Showing papers in "Mobile Information Systems in 2015"
TL;DR: This paper presents a new 802.11-based indoor positioning method using support vector regression (SVR), which consists of offline training stage and online location stage, and shows that the proposed method has a higher positioning accuracy compared with the probability and neutral network method.
Abstract: The wide spread of the 802.11-based wireless technology brings about a good opportunity for the indoor positioning system. In this paper, we present a new 802.11-based indoor positioning method using support vector regression (SVR), which consists of offline training stage and online location stage. The model that describes the relations between the position and the received signal strength (RSS) of the mobile device is established at the offline training stage by SVR, and at the online location stage the exact position is determined by this model. Due to the complex indoor environment, RSS is vulnerable and changeable. To address this issue, data filtering rules obtained through statistical analysis are applied at offline training stage to improve the quality of training samples and thus improve the quality of prediction model. At the online location stage, -times continuous measurement is utilized to obtain the high quality RSS input, which guarantees the consistency with the training samples and improves the position accuracy of mobile devices. Performance evaluation shows that the proposed method has a higher positioning accuracy compared with the probability and neutral network method, and the demand for the storage capacity and computing power is also low at the same time.
43 citations
TL;DR: This paper analyses the principle of software-defined networking and presents a new probabilistic method of load balancing based on variance analysis which has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.
Abstract: In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN) and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data traffic of each port by means of variance analysis and provides a probability-based selection algorithm to redirect traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.
30 citations
TL;DR: In this paper a routing protocol is proposed by considering the Quality of Service requirements of the body area network data packets, and a mechanism for handling delay-sensitive packets is provided by this protocol.
Abstract: Consistent performance, energy efficiency, and reliable transfer of data are critical factors for real-time monitoring of a patient’s data, especially in a hospital environment. In this paper, a routing protocol is proposed by considering the QoS requirements of the Body Area Network (BAN) data packets. A mechanism for handling delay-sensitive packets is provided by this protocol. Moreover, linear programming based modeling along with graphical analysis is also done. Extensive simulations using the OMNeT
26 citations
TL;DR: It is shown that the optimal throughput of the EHCN is critically dependent on time switching and power splitting factor of the TPSR protocol, and the tightness of the proposed protocol is determined through Monte Carlo simulation results.
Abstract: We propose a new protocol for energy harvesting at relay mobile node in wireless communications called energy harvesting cooperative networks (EHCN). In particular, we investigate how the harvested power at relay mobile node affects outage probability and throughput performance. Specifically, we develop outage and throughput performance characterizations in terms of time and power factors in the proposed time power switching based relaying (TPSR) protocol. A simple, highly accurate closed-form formula of outage probability is also derived. It is shown that the optimal throughput of the EHCN is critically dependent on time switching and power splitting factor of the TPSR protocol. In addition, we extend the proposed protocol performance in ideal case of receiver. The tightness of our proposed protocol is determined through Monte Carlo simulation results. Finally, our results provide useful guidelines for the design of the energy harvesting enabled relay mobile node in the EHCN.
26 citations
TL;DR: The ecosystem metaphor for WSNs is explored and an agent-based architecture that migrates complex processing tasks outside the physical sensor network while incorporating missing characteristics of autonomy, intelligence, and context awareness to the WSN is proposed.
Abstract: Wireless sensor networks (WSNs) are key components in the emergent cyber physical systems (CPSs). They may include hundreds of spatially distributed sensors which interact to solve complex tasks going beyond their individual capabilities. Due to the limited capabilities of sensors, sensor actions cannot meet CPS requirements while controlling and coordinating the operations of physical and engineered systems. To overcome these constraints, we explore the ecosystem metaphor for WSNs with the aim of taking advantage of the efficient adaptation behavior and communication mechanisms of living organisms. By mapping these organisms onto sensors and ecosystems onto WSNs, we highlight shortcomings that prevent WSNs from delivering the capabilities of ecosystems at several levels, including structure, topology, goals, communications, and functions. We then propose an agent-based architecture that migrates complex processing tasks outside the physical sensor network while incorporating missing characteristics of autonomy, intelligence, and context awareness to the WSN. Unlike existing works, we use software agents to map WSNs to natural ecosystems and enhance WSN capabilities to take advantage of bioinspired algorithms. We extend our architecture and propose a new intelligent CPS framework where several control levels are embedded in the physical system, thereby allowing agents to support WSNs technologies in enabling CPSs.
23 citations
TL;DR: This work aims to respond to the development of applications as well as the services for mobile systems by developing a computational model that formalizes the problem and that defines adjusting computing methods to meet productivity and quality of desired services.
Abstract: The development of applications as well as the services for mobile systems faces a varied range of devices with very heterogeneous capabilities whose response times are difficult to predict. The research described in this work aims to respond to this issue by developing a computational model that formalizes the problem and that defines adjusting computing methods. The described proposal combines imprecise computing strategies with cloud computing paradigms in order to provide flexible implementation frameworks for embedded or mobile devices. As a result, the imprecise computation scheduling method on the workload of the embedded system is the solution to move computing to the cloud according to the priority and response time of the tasks to be executed and hereby be able to meet productivity and quality of desired services. A technique to estimate network delays and to schedule more accurately tasks is illustrated in this paper. An application example in which this technique is experimented in running contexts with heterogeneous work loading for checking the validity of the proposed model is described.
23 citations
TL;DR: Simulation results demonstrate that the parameters that affect the choice of a CSMA-CA MAC layer protocol are end-to-end delay and packet loss requirements of a real-time multimedia flow, data load within the interference range of transmitters along the forwarding path, and length of the Forwarding path.
Abstract: Real-time multimedia applications require quality of service (QoS) provisioning in terms of bounds on delay and packet loss along with soft bandwidth guarantees. The shared nature of the wireless communication medium results in interference. Interference combined with the overheads, associated with a medium access control (MAC) protocol, and the implementation of a networking protocol stack limit the available bandwidth in IEEE 802.15.4-based networks and can result in congestion, even if the transmission rates of nodes are well below the maximum bandwidth supported by an underlying communication technology. Congestion degrades the performance of admitted real-time multimedia flow(s). Therefore, in this paper, we experimentally derive the IEEE 802.15.4 channel capacity using an unslotted CSMA-CA MAC protocol. We experimentally derive channel capacity for two cases, that is, when the CSMA-CA protocol is working without ACKs and when it is working with ACKs. Moreover, for both cases, we plot the relationship of offered data load with delay and packet loss rate. Simulation results demonstrate that the parameters that affect the choice of a CSMA-CA MAC layer protocol are end-to-end delay and packet loss requirements of a real-time multimedia flow, data load within the interference range of transmitters along the forwarding path, and length of the forwarding path.
23 citations
TL;DR: This work proposes using the social network information of a node when performing routing, since a node is more likely to encounter members of its own social community than other nodes, and improves the solution by adding a selfish node detection and avoidance mechanism.
Abstract: Since mobile devices nowadays have become ubiquitous, several types of networks formed over such devices have been proposed One such approach is represented by opportunistic networking, which is based on a store-carry-and-forward paradigm, where nodes store data and carry it until they reach a suitable node for forwarding The problem in such networks is how to decide what the next hop will be, since nodes do not have a global view of the network We propose using the social network information of a node when performing routing, since a node is more likely to encounter members of its own social community than other nodes
In addition, we approximate a node’s contact as a Poisson distribution and show that we can predict its future behavior based on the contact history Furthermore, since opportunistic network nodes may be selfish, we improve our solution by adding a selfish node detection and avoidance mechanism, which can help reduce the number of unnecessary messages sent in the network, and thus avoid congestion and decrease battery consumption We show that our algorithm outperforms existing solutions such as BUBBLE Rap and Epidemic in terms of delivery cost and hit rate, as well as the rate of congestion introduced in the network, by testing in various realistic scenarios
22 citations
TL;DR: Optimal strategies to save IDS agents’ power, through Quantal Response Equilibrium (QRE) that is more realistic than Nash Equilibrium are obtained and thus the IDS can respond correspondingly to protect WSNs.
Abstract: This paper is to solve the problem stating that applying Intrusion Detection System (IDS) to guarantee security of Wireless Sensor Networks (WSNs) is computationally costly for sensor nodes due to their limited resources. For this aim, we obtain optimal strategies to save IDS agents’ power, through Quantal Response Equilibrium (QRE) that is more realistic than Nash Equilibrium. A stage Intrusion Detection Game (IDG) is formulated to describe interactions between the Attacker and IDS agents. The preference structures of different strategy profiles are analyzed. Upon these structures, the payoff matrix is obtained. As the Attacker and IDS agents interact continually, the stage IDG is extended to a repeated IDG and its payoffs are correspondingly defined. The optimal strategies based on QRE are then obtained. These optimal strategies considering bounded rationality make IDS agents not always be in Defend. Sensor nodes’ power consumed in performing intrusion analyses can thus be saved. Experiment results show that the probabilities of the actions adopted by the Attacker can be predicted and thus the IDS can respond correspondingly to protect WSNs.
19 citations
TL;DR: A degree of hiding intention for the mobile application (app) to keep its leaking activity invisible to the user is measured to assist a malware detection system in reducing the rate of false positive by considering malicious intentions.
Abstract: To overcome the resource and computing power limitation of mobile devices in Internet of Things (IoT) era, a cloud computing provides an effective platform without human intervention to build a resource-oriented security solution. However, existing malware detection methods are constrained by a vague situation of information leaks. The main goal of this paper is to measure a degree of hiding intention for the mobile application (app) to keep its leaking activity invisible to the user. For real-world application test, we target Android applications, which unleash user privacy data. With the TaintDroid-ported emulator, we make experiments about the timing distance between user events and privacy leaks. Our experiments with Android apps downloaded from the Google Play show that most of leak cases are driven by user explicit events or implicit user involvement which make the user aware of the leakage. Those findings can assist a malware detection system in reducing the rate of false positive by considering malicious intentions. From the experiment, we understand better about app’s internal operations as well. As a case study, we also presents a cloud-based dynamic analysis framework to perform a traffic monitor.
18 citations
TL;DR: This paper proposes an energy efficient and safe weighted clustering algorithm (ES-WCA) for mobile WSNs using a combination of five metrics which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node.
Abstract: The main concern of clustering approaches for mobile wireless sensor networks (WSNs) is to prolong the battery life of the individual sensors and the network lifetime. For a successful clustering approach the need of a powerful mechanism to safely elect a cluster head remains a challenging task in many research works that take into account the mobility of the network. The approach based on the computing of the weight of each node in the network is one of the proposed techniques to deal with this problem. In this paper, we propose an energy efficient and safe weighted clustering algorithm (ES-WCA) for mobile WSNs using a combination of five metrics. Among these metrics lies the behavioral level metric which promotes a safe choice of a cluster head in the sense where this last one will never be a malicious node. Moreover, the highlight of our work is summarized in a comprehensive strategy for monitoring the network, in order to detect and remove the malicious nodes. We use simulation study to demonstrate the performance of the proposed algorithm.
TL;DR: It is concluded that standardized mobile business apps cannot meet the different requirements of various groups of mobile workers, as task- and firm-specific (individualized) requirements determine the specification, implementation, and application of mobile apps.
Abstract: In recent years, the diffusion of mobile applications (mobile apps) has risen significantly. Nowadays, mobile business apps are strongly emerging in business, enhancing productivity and employees’ satisfaction, whilst the usage of customized individual enterprise apps is still an exception. Standardized business apps enable basic functionalities, for example, mobile data storage and exchange (e.g., Dropbox), communication (e.g., Skype), and other routine processes, which support mobile workers. In addition, mobile apps can, for example, increase the flexibility of mobile workers by easing the access to firm’s information from outside the enterprise and by enabling ubiquitous collaboration. Hence, mobile apps can generate competitive advantages and can increase work efficiency on a broad scale. But mobile workers form no coherent group. Our research reveals, based on two case studies, that they can be clustered into two groups: knowledge workers and field workers. Knowledge workers and field workers fulfill different tasks and work in different environments. Hence, they have different requirements for mobile support. In this paper we conclude that standardized mobile business apps cannot meet the different requirements of various groups of mobile workers. Task- and firm-specific (individualized) requirements determine the specification, implementation, and application of mobile apps.
TL;DR: The proposed fuzzy-based power saving scheduling scheme for IoT over the LTE/LTE-Advanced networks can meet the requirements of the DRX cycle and scheduling latency and can save about half of energy consumption for IoT devices compared to conventional approaches.
Abstract: The devices of Internet of Things (IoT) will grow rapidly in the near future, and the power consumption and radio spectrum management will become the most critical issues in the IoT networks. Long Term Evolution (LTE) technology will become a promising technology used in IoT networks due to its flat architecture, all-IP network, and greater spectrum efficiency. The 3rd Generation Partnership Project (3GPP) specified the Discontinuous Reception (DRX) to reduce device’s power consumption. However, the DRX may pose unexpected communication delay due to missing Physical Downlink Control Channel (PDCCH) information in sleep mode. Recent studies mainly focus on optimizing DRX parameters to manage the tradeoff between the energy consumption and communication latency. In this paper, we proposed a fuzzy-based power saving scheduling scheme for IoT over the LTE/LTE-Advanced networks to deal with the issues of the radio resource management and power consumption from the scheduling and resource allocation perspective. The proposed scheme considers not only individual IoT device’s real-time requirement but also the overall network performance. The simulation results show that our proposed scheme can meet the requirements of the DRX cycle and scheduling latency and can save about half of energy consumption for IoT devices compared to conventional approaches.
TL;DR: A distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph.
Abstract: In WSNs the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting simultaneously. Such a situation is known as spatially correlated contention. The random access method to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration, and therefore generating an optimal or suboptimal schedule is not very useful. Additionally, if an algorithm takes very long time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. In this paper, we present a distributed TDMA slot scheduling (DTSS) algorithm, which considerably reduces the time required to perform scheduling, while restricting the schedule length to the maximum degree of interference graph. The DTSS algorithm supports unicast, multicast, and broadcast scheduling, simultaneously without any modification in the protocol. We have analyzed the protocol for average case performance and also simulated it using Castalia simulator to evaluate its runtime performance. Both analytical and simulation results show that our protocol is able to considerably reduce the time required for scheduling.
TL;DR: A new cross layer fine-grained architecture called named data networking for cognitive radio ad hoc networks (NDN-CRAHNs) is proposed which provides distinct features such as in-networking caching, security, scalability, and multipath routing.
Abstract: Named data networking (NDN) is a newly proposed paradigm for future Internet, in which communication among nodes is based on data names, decoupling from their locations. In dynamic and self-organized cognitive radio ad hoc networks (CRAHNs), it is difficult to maintain end-to-end connectivity between ad hoc nodes especially in the presence of licensed users and intermittent wireless channels. Moreover, IP-based CRAHNs have several issues like scalability, inefficient-mapping, poor resource utilization, and location dependence. By leveraging the advantages of NDN, in this paper, we propose a new cross layer fine-grained architecture called named data networking for cognitive radio ad hoc networks (NDN-CRAHNs). The proposed architecture provides distinct features such as in-networking caching, security, scalability, and multipath routing. The performances of the proposed scheme are evaluated comparing to IP-based scheme in terms of average end-to-end delay and packet delivery ratio. Simulation results show that the proposed scheme is effective in terms of average contents download time and packet delivery ratios comparing to conventional cognitive radio ad hoc networks.
TL;DR: An enhanced VFDT (EVFDT) is proposed to efficiently detect the occurrence of DDoS attack in cloud-assisted WBAN using an adaptive tie-breaking threshold for node splitting and a lightweight iterative pruning technique.
Abstract: Due to the scattered nature of DDoS attacks and advancement of new technologies such as cloud-assisted WBAN, it becomes challenging to detect malicious activities by relying on conventional security mechanisms. The detection of such attacks demands an adaptive and incremental learning classifier capable of accurate decision making with less computation. Hence, the DDoS attack detection using existing machine learning techniques requires full data set to be stored in the memory and are not appropriate for real-time network traffic. To overcome these shortcomings, Very Fast Decision Tree (VFDT) algorithm has been proposed in the past that can handle high speed streaming data efficiently. Whilst considering the data generated by WBAN sensors, noise is an obvious aspect that severely affects the accuracy and increases false alarms. In this paper, an enhanced VFDT (EVFDT) is proposed to efficiently detect the occurrence of DDoS attack in cloud-assisted WBAN. EVFDT uses an adaptive tie-breaking threshold for node splitting. To resolve the tree size expansion under extreme noise, a lightweight iterative pruning technique is proposed. To analyze the performance of EVFDT, four metrics are evaluated: classification accuracy, tree size, time, and memory. Simulation results show that EVFDT attains significantly high detection accuracy with fewer false alarms.
TL;DR: This work presents an efficient approach to service selection based on computing QoS uncertainty that achieves the best solution in two senses: the time cost for finding the best services is short and the reliability of the selected services is high.
Abstract: With the rapid development of mobile wireless networks such as 4G and LET, ever more mobile services and applications are emerging in mobile networks. Faced with massive mobile services, a top priority of mobile information systems is how to find the best services and compose them into new value-added services (e.g., location-based services). Hence, service selection is one of the most fundamental operations in mobile information systems. Traditional implementation of service selection suffers from the problems of a huge number of services and reliability. We present an efficient approach to service selection based on computing QoS uncertainty that achieves the best solution in two senses: (1) the time cost for finding the best services is short and (2) the reliability of the selected services is high. We have implemented our approach in experiments with real-world and synthetic datasets. Our results show that our approach improves on the other approaches tested.
TL;DR: A novel wayfinding system adapted to people with cognitive disabilities that divides the calculated route into atomic instructions and uses street-level photographs at the decision points improves users’ performance in terms of the number who reached the destination and were able to identify it correctly.
Abstract: This paper presents a novel wayfinding system adapted to people with cognitive disabilities. It adapts to the user in terms of route calculation, instructions delivery, and interface design. To do so, the system divides the calculated route into atomic instructions and uses street-level photographs at the decision points. To evaluate this approach, we compared it with a commercial navigation application on a field trial with a sample of users (N = 18). From the evaluation, we concluded that our system improves users’ performance in terms of the number who reached the destination and were able to identify it correctly.
TL;DR: This work surveys some of the recent research activities in Doppler shift compensation schemes and highlights challenges and solutions as a stock-taking exercise, and presents open issues to be further investigated in order to address the challenges of Dopplers shift in VANETs.
Abstract: Over the last decade vehicle-to-vehicle (V2V) communication has received a lot of attention as it is a crucial issue in intravehicle communication as well as in Intelligent Transportation System (ITS). In ITS the focus is placed on integration of communication between mobile and fixed infrastructure to execute road safety as well as nonsafety information dissemination. The safety application such as emergence alerts lays emphasis on low-latency packet delivery rate (PDR), whereas multimedia and infotainment call for high data rates at low bit error rate (BER). The nonsafety information includes multimedia streaming for traffic information and infotainment applications such as playing audio content, utilizing navigation for driving, and accessing Internet. A lot of vehicular ad hoc network (VANET) research has focused on specific areas including channel multiplexing, antenna diversity, and Doppler shift compensation schemes in an attempt to optimize BER performance. Despite this effort few surveys have been conducted to highlight the state-of-the-art collection on Doppler shift compensation schemes. Driven by this cause we survey some of the recent research activities in Doppler shift compensation schemes and highlight challenges and solutions as a stock-taking exercise. Moreover, we present open issues to be further investigated in order to address the challenges of Doppler shift in VANETs.
TL;DR: In this paper, the authors proposed a fair secure computation protocol in mobile social networks, in which rational parties have incentives to implement the applications for a higher utility in the presence of two rational parties.
Abstract: With the rapid development of mobile devices and wireless technologies, mobile social networks become increasingly available. People can implement many applications on the basis of mobile social networks. Secure computation, like exchanging information and file sharing, is one of such applications. Fairness in secure computation, which means that either all parties implement the application or none of them does, is deemed as an impossible task in traditional secure computation without mobile social networks. Here we regard the applications in mobile social networks as specific functions and stress on the achievement of fairness on these functions within mobile social networks in the presence of two rational parties. Rational parties value their utilities when they participate in secure computation protocol in mobile social networks. Therefore, we introduce reputation derived from mobile social networks into the utility definition such that rational parties have incentives to implement the applications for a higher utility. To the best of our knowledge, the protocol is the first fair secure computation in mobile social networks. Furthermore, it finishes within constant rounds and allows both parties to know the terminal round.
TL;DR: This paper proposes a lightweight hierarchical cluster-based location service in city environments (HCBLS), which integrates a logical clustering based on the city digital map and consequently does not involve extra signaling overhead.
Abstract: Vehicle location information is central to many location-based services and applications in VANETs. Tracking vehicles positions and maintaining an accurate up-to-date view of the entire network are not easy due to the high mobility of vehicles and consequently rapid topology changes. The design of a scalable, accurate, and efficient location service is still a very challenging issue. In this paper, we propose a lightweight hierarchical cluster-based location service in city environments (HCBLS). HCBLS integrates a logical clustering based on the city digital map and consequently does not involve extra signaling overhead. An advanced location update aggregation at different levels of the assumed hierarchy is adopted to maintain up-to-date and accurate location information. Simulation results show that HCBLS achieves much better performances than the Efficient Map-Based Location Service (EMBLS) and any regular (non-cluster-based) updating scheme. HCBLS increases the success rate by around 10%, improves the overview of the network by more than 30%, lowers the location update and query costs by more than 7 times, lowers the message delivery latency by around 3 times, and presents around 4 times better localization accuracy.
TL;DR: A vertical handover scheme for handover triggering and selection of an appropriate network is proposed that efficiently optimizes the handoff related parameters, and it shows significant improvement in the existing models used for similar purpose.
Abstract: Machine-to-Machine (M2M) communications framework is evolving to sustain faster networks with the potential to connect millions of devices in the following years. M2M is one of the essential competences for implementing Internet of Things (IoT). Therefore, various organizations are now focusing on enhancing improvements into their standards to support M2M communications. Thus, Heterogeneous Mobile Ad Hoc Network (HetMANET) can normally be considered appropriate for M2M challenges. These challenges incorporated when a mobile node (MN) selects a target network in an energy efficient scanning for efficient handover. Therefore, to cope with these constraints, we proposed a vertical handover scheme for handover triggering and selection of an appropriate network. The proposed scheme is composed of two phases. Firstly, the MNs perform handover triggering based on the optimization of the Receive Signal Strength (RSS) from an access point/base station (AP/BS). Secondly, the network selection process is performed by considering the cost and energy consumption of a particular application during handover. Moreover, if there are more networks available, then the MN selects the one provided with the highest quality of service (QoS). The decision regarding the selection of available networks is made on three metrics, that is, cost, energy, and data rate. Furthermore, the selection of an AP/BS of the selected network is made on five parameters: delay, jitter, Bit Error Rate (BER), communication cost, and response time. The numerical and experimental results are compared in the context of energy consumption by an MN, traffic management on an AP/BS, and QoS of the available networks. The proposed scheme efficiently optimizes the handoff related parameters, and it shows significant improvement in the existing models used for similar purpose.
TL;DR: The proposed frame size adaptation scheme is fully compatible with the IEEE 802.11 standard and works in a distributed manner, which neither modifies the channel access mechanism nor resorts to a centralized scheduling algorithm.
Abstract: This paper deals with the problem of performance degradation in wireless local area networks (WLANs) based on IEEE 802.11n. When a wireless channel is shared by heterogeneous stations that have different data rates and packet sizes,
each station occupies a different amount of airtime because the basic channel access mechanism of WLAN was originally designed
to provide fair chance of channel access, regardless of packet size and data rate. This leads to the degradation of overall network throughput and airtime fairness among stations, which is known as performance anomaly. To resolve this problem, we firstly formulate an optimization problem for a generalized two-level frame aggregation whose objective is to maximize the achievable throughput under the constraint of airtime fairness. Then, we propose a frame size adaptation scheme that controls the number of packets in an aggregated frame. The proposed scheme is fully compatible with the IEEE 802.11 standard and works in a distributed manner, which neither modifies the channel access mechanism nor resorts to a centralized scheduling algorithm. The extensive simulation results confirm that the proposed scheme tightly regulates the airtime usage of each station to be almost the same
and significantly improves the overall network throughput compared to other existing schemes.
TL;DR: A new wireless resource mapping algorithm for saving energy in ultradense small cells has been put forward and it is demonstrated that the algorithm can effectively reduce the system energy consumption and required wireless resource amount under the condition of satisfying users’ QoS.
Abstract: As the current network is designed for peak loads, it results in insufficient resource utilization and energy waste. Virtualized technology makes it possible that intelligent energy perception network could be deployed and resource sharing could become an effective energy saving technology. How to make more small cells into sleeping state for energy saving in ultradense small cell system has become a research hot spot. Based on the mapping feature of virtualized network, a new wireless resource mapping algorithm for saving energy in ultradense small cells has been put forward when wireless resource amount is satisfied in every small cell. First of all, the method divides the virtual cells. Again through the alternate updating between small cell mapping and wireless resource allocation, least amount of small cells is used and other small cells turn into sleeping state on the premise of guaranteeing users’ QoS. Next, the energy consumption of the wireless access system, wireless resource utilization, and the convergence of the proposed algorithm are analyzed in theory. Finally, the simulation results demonstrate that the algorithm can effectively reduce the system energy consumption and required wireless resource amount under the condition of satisfying users’ QoS.
TL;DR: The Bipolar Traffic Density Awareness Routing (BTDAR) protocol aims at providing reliable and efficient packets delivery for dense and sparse vehicle traffic network environments.
Abstract: To support an increasing amount of various new applications in vehicular ad hoc networks (VANETs), routing protocol design has become an important research challenge. In this paper, we propose a Bipolar Traffic Density Awareness Routing (BTDAR) protocol for vehicular ad hoc networks. The BTDAR aims at providing reliable and efficient packets delivery for dense and sparse vehicle traffic network environments. Two distinct routing protocols are designed to find an optimal packet delivery path in varied vehicular networks. In dense networks, a link-stability based routing protocol is designed to take vehicles connectivity into consideration in its path selection policy and maximize the stability of intervehicle communications. In sparse networks, a min-delay based routing protocol is proposed to select an optimal route by analyzing intermittent vehicle connectivity and minimize packets delivery latency. Intervehicles connectivity model is analyzed. The performance of BTDAR is examined by comparisons with three distinct VANET routing protocols. Simulation results show that the BTDAR outperforms compared counterpart routing protocols in terms of packet delivery delay and packet delivery ratio.
TL;DR: A basic key management protocol is described for WSNs based on four kinds of keys, which can be derived from an initial master key, and an enhanced protocol is proposed based on Diffie-Hellman algorithm, which meets the requirement of energy efficiency by supporting in-network processing.
Abstract: With rapid development and extensive use of wireless sensor networks (WSNs), it is urgent to enhance the security for WSNs, in which key management is an effective way to protect WSNs from various attacks. However, different types of messages exchanged in WSNs typically have different security requirements which cannot be satisfied by a single keying mechanism. In this study, a basic key management protocol is described for WSNs based on four kinds of keys, which can be derived from an initial master key, and an enhanced protocol is proposed based on Diffie-Hellman algorithm. The proposed scheme restricts the adverse security impact of a captured node to the rest of WSNs and meets the requirement of energy efficiency by supporting in-network processing. The master key protection, key revocation mechanism, and the authentication mechanism based on one-way hash function are, respectively, discussed. Finally, the performance of the proposed scheme is analyzed from the aspects of computational efficiency, storage requirement and communication cost, and its antiattack capability in protecting WSNs is discussed under various attack models. In this paper, promising research directions are also discussed.
TL;DR: An efficient scheme to estimate the number of unidentified tags for Dynamic Framed Slotted Aloha (DFSA) based RFID system, with the view of increasing system performance and promoting business effectiveness and efficiency.
Abstract: Radio Frequency IDentification (RFID) used in business applications and international business management fields can create and sustain the competitive advantage, which is also one of the wireless telecommunication techniques for recognizing objects to realize Internet of Things (IoT) technologies. In construction of IoT network, the RFID technologies play the role of the front-end data collection via tag identification, as the basis of IoT. Hence, the adoption of RFID technologies is spurring innovation and the development of the IoT. However, in RFID system, one of the most important challenges is the collision resolution between the tags when these tags transmit their data to the reader simultaneously. Hence, in this paper I develop an efficient scheme to estimate the number of unidentified tags for Dynamic Framed Slotted Aloha (DFSA) based RFID system, with the view of increasing system performance. In addition to theoretical analysis, simulations are conducted to evaluate the performance of proposed scheme. The simulation results reveal the proposed scheme works very well in providing a substantial performance improvement in RFID system. The proposed algorithm promotes business effectiveness and efficiency while applying the RFID technologies to IoT.
TL;DR: A novel methodology based on multicriterion decision making and fuzzy classification that can provide a viable second-line of defense for mitigating cyber-attacks is investigated and augmented with a genetic attribute selection strategy.
Abstract: With the proliferation of wireless and mobile network infrastructures and capabilities, a wide range of exploitable vulnerabilities emerges due to the use of multivendor and multidomain cross-network services for signaling and transport of Internet- and wireless-based data. Consequently, the rates and types of cyber-attacks have grown considerably and current security countermeasures for protecting information and communication may be no longer sufficient. In this paper, we investigate a novel methodology based on multicriterion decision making and fuzzy classification that can provide a viable second-line of defense for mitigating cyber-attacks. The proposed approach has the advantage of dealing with various types and sizes of attributes related to network traffic such as basic packet headers, content, and time. To increase the effectiveness and construct optimal models, we augmented the proposed approach with a genetic attribute selection strategy. This allows efficient and simpler models which can be replicated at various network components to cooperatively detect and report malicious behaviors. Using three datasets covering a variety of network attacks, the performance enhancements due to the proposed approach are manifested in terms of detection errors and model construction times.
TL;DR: This paper proposes a verifiable rational secret sharing scheme in mobile networks that provides a noninteractively verifiable proof for the correctness of participants’ share and handshake protocol and the security of the scheme relies on a computational assumption.
Abstract: With the development of mobile network, lots of people now have access to mobile phones and the mobile networks give users ubiquitous connectivity. However, smart phones and tablets are poor in computational resources such as memory size, processor speed, and disk capacity. So far, all existing rational secret sharing schemes cannot be suitable for mobile networks. In this paper, we propose a verifiable rational secret sharing scheme in mobile networks. The scheme provides a noninteractively verifiable proof for the correctness of participants’ share and handshake protocol is not necessary; there is no need for certificate generation, propagation, and storage in the scheme, which is more suitable for devices with limited size and processing power; in the scheme, every participant uses her encryption on number of each round as the secret share and the dealer does not have to distribute any secret share; every participant cannot gain more by deviating the protocol, so rational participant has an incentive to abide by the protocol; finally, every participant can obtain the secret fairly (means that either everyone receives the secret, or else no one does) in mobile networks. The scheme is coalition-resilient and the security of our scheme relies on a computational assumption.
TL;DR: A hybrid control mechanism that integrates contention window control and frame aggregation is proposed that significantly increases the overall throughput by about three times compared to the conventional DCF, while assuring airtime fairness strictly.
Abstract: The IEEE 802.11 standard has been evolved to support multiple transmission rates in wireless local area networks (WLANs) to cope with diverse channel conditions and to increase throughput. However, when stations with different transmission rates coexist, the basic channel access mechanism of WLAN, distributed coordination function (DCF), not only fails to assure airtime fairness among competing stations but also decreases overall network throughput, because DCF was designed to provide fair opportunity of channel access, regardless of transmission rate. As an effective solution to this problem, we propose a hybrid control mechanism that integrates contention window control and frame aggregation. The former adjusts the size of contention window and differentiates the channel access opportunity depending on the transmission rates of stations. The latter controls the number of packets in the aggregated frame to tightly assure per-station airtime fairness with the reduced channel access overheads. Moreover, we derive an analytical model to evaluate the performance of the proposed mechanism in terms of throughput and fairness. Along with the analysis results, the extensive simulation results confirm that the proposed mechanism significantly increases the overall throughput by about three times compared to the conventional DCF, while assuring airtime fairness strictly.