Showing papers in "Mobile Networks and Applications in 2015"

Software-Defined and Virtualized Future Mobile and Wireless Networks: A Survey

Abstract: With the proliferation of mobile demands and increasingly multifarious services and applications, mobile Internet has been an irreversible trend. Unfortunately, the current mobile and wireless network (MWN) faces a series of pressing challenges caused by the inherent design. In this paper, we extend two latest and promising innovations of Internet, software-defined networking and network virtualization, to mobile and wireless scenarios. We first describe the challenges and expectations of MWN, and analyze the opportunities provided by the software-defined wireless network (SDWN) and wireless network virtualization (WNV). Then, this paper focuses on SDWN and WNV by presenting the main ideas, advantages, ongoing researches and key technologies, and open issues respectively. Moreover, we interpret that these two technologies highly complement each other, and further investigate efficient joint design between them. This paper confirms that SDWN and WNV may efficiently address the crucial challenges of MWN and significantly benefit the future mobile and wireless network.

Cloud-based Wireless Network: Virtualized, Reconfigurable, Smart Wireless Network to Enable 5G Technologies

Abstract: In recent years, information communication and computation technologies are deeply converging, and various wireless access technologies have been successful in deployment. It can be predicted that the upcoming fifth generation mobile communication technology (5G) can no longer be defined by a single business model or a typical technical characteristic. 5G is a multi-service and multi-technology integrated network, meeting the future needs of a wide range of big data and the rapid development of numerous businesses, and enhancing the user experience by providing smart and customized services. In this paper, we propose a cloud-based wireless network architecture with four components, i.e., mobile cloud, cloud-based radio access network (Cloud RAN), reconfigurable network and big data centre, which is capable of providing a virtualized, reconfigurable, smart wireless network.

Cloud-Assisted Speech and Face Recognition Framework for Health Monitoring

Abstract: The increasing demand for the remote monitoring of patients combined with the promising potential of cloud computing has enabled the design and development of a number of cloud-based systems and services for healthcare. The cloud computing, in combination with the popularity of smart handheld devices, has inspired healthcare professionals to remotely monitor patients' health while the patient is at home. To this end, this paper proposes a cloud-assisted speech and face recognition framework for elderly health monitoring, where handheld devices or video cameras collect speech along with face images and deliver to the cloud server for possible analysis and classification. In the framework, a patient's state such as pain, tensed, and so forth is recognized from his or her speech and face images. The patient state recognition system extracts local features from speech, and texture descriptors from face images. Then it classifies using support vector machines. The recognized state is later sent to the remote care center, healthcare professionals and providers for necessary services in order to provide seamless health monitoring. Experiments have been performed to validate the approach and to evaluate the suitability of this framework in terms of accuracy and time requirements. The results demonstrate the effectiveness of the proposed approach with regards to face and speech processing.

CADRE: Cloud-Assisted Drug REcommendation Service for Online Pharmacies

Abstract: With the development of e-commerce, a growing number of people prefer to purchase medicine online for the sake of convenience. However, it is a serious issue to purchase medicine blindly without necessary medication guidance. In this paper, we propose a novel cloud-assisted drug recommendation (CADRE), which can recommend users with top-N related medicines according to symptoms. In CADRE, we first cluster the drugs into several groups according to the functional description information, and design a basic personalized drug recommendation based on user collaborative filtering. Then, considering the shortcomings of collaborative filtering algorithm, such as computing expensive, cold start, and data sparsity, we propose a cloud-assisted approach for enriching end-user Quality of Experience (QoE) of drug recommendation, by modeling and representing the relationship of the user, symptom and medicine via tensor decomposition. Finally, the proposed approach is evaluated with experimental study based on a real dataset crawled from Internet.

Suboptimal Beam Search Algorithm and Codebook Design for Millimeter-Wave Communications

Abstract: In order to improve the efficiency of beamforming for millimeter-wave communications, a codebook is designed and a corresponding beam search algorithm is proposed in this paper. The codebook is designed with a feature of hierarchy, and can be organized into a binary tree, which makes the implementation of binary search possible. Meanwhile, based on the designed codebook, a suboptimal binary search like (BSL) algorithm is proposed for beamforming. Theoretical analysis and simulation results show that, compared with the state-of-the-art search schemes, the proposed scheme dramatically decreases the search time.

Optimal Energy Strategy for Node Selection and Data Relay in WSN-based IoT

Abstract: Datacollection and dissemination in wireless sensor networks (WSN) for Internet of Things (IoT) require stable multi-hop networking path from source to sink. However, due to the limited energy capacity, relay nodes that run out of battery may cause disconnected path and result in failure of end-to-end data transmission in WSN-based IoT. Therefore, besides saving energy in itself, each sensor involved in the multi-hop transmission activity also needs a feasible strategy to select the relay nodes by leveraging their residual energy and multi-hop IoT network connectivity. In this paper, we first analyze energy consumption model and data relay model in WSN-based IoT, and then propose the concept of "equivalent node" to select relay node for optimal data transmission and energy conservation. A probabilistic dissemination algorithm, called ENS_PD, is designed to choose the optimal energy strategy and prolong the lifetime of whole network. Extensive simulation and real testbed results show that our models and algorithms can minimize energy consumption while guarantee the quality of communication in WSN-based IoT in comparison with other methods.

Dynamic Spectrum Access Algorithm Based on Game Theory in Cognitive Radio Networks

Abstract: As an enabling technology for dynamic spectrum access (DSA), cognitive radio (CR) is widely regarded as one of the most promising technologies for future the fifth generation (5G) wireless communications Although there have been significant prior researches to combat interference on primary users (PUs), the problem of mitigating mutual interference between secondary users (SUs), -which is tightly coupled with SU's spectrum leasing- is still not understood well This paper proposes a DSA algorithm based on game theory, which jointly performs spectrum leasing and interference mitigation among SUs The problem is modeled as an oligopolistic competition using Stackelberg model We have carefully studied the SU's spectrum utilization behavior with respect to various criteria of the proposed game theoretic model Simulation results shows that, Compared with Cournot game model, the proposed scheme enables SUs to efficiently utilize the licensed spectrum shared with PUs in a dynamic environment while maximizing the spectrum utilization

Design and Implementation of a Software-Defined Mobility Architecture for IP Networks

Abstract: Recently many research efforts have been spent on applying Software Defined Networking (SDN) to mobile and wireless networking to make them adapt to the rapid development and popularity of the mobile Internet. SDN offers programmable devices and centralized control which help to realize customizable and adaptive solutions to meet requirements from diversified mobile networks, devices, applications and so forth. This paper focuses on extending SDN paradigm to mobility handling in the Internet which has been little studied, and proposes design, implementation and deployment of a software-defined IP mobility architecture. The paper also demonstrates evaluations and experiments of the proposal based on both the Mininet platform and a cross-domain SDN testbed. Results prove the feasibility, scalability and high adaptability of the proposal.

Real-time Event Detection on Social Data Stream

Abstract: Social Network Services (SNS) are becoming more popular in our daily life, the process is boosted by various kinds of smart devices integrating utility modules such as 3G/WIFI connector, GPS tracker, Camera, Heartbeat sensor and so on. It makes the information flow (or Social Data Stream) on SNS have a real-time nature characteristic, where each SNS user is an information sensor and also a data connector for diffusing interesting news to his/her communication networks. Hiding inside the information flow are pieces of real social events. The events draw attention from users evidencing by the number of relevant announces and communication interactions toward that topic. However, traditional topic detection approaches are not designed to detect the kind of the event efficiently in real-time, particularly if the data sources are influenced by noise data and containing diverse topics. To overcome the issue, in this paper we proposed a model for extracting and tracking real social events on Social Data Stream, which can work well in real-time by using distributing computation and data aggregation technique on the discrete signals as a new representation of the original data.

Weighted Similarity Schemes for High Scalability in User-Based Collaborative Filtering

Abstract: Similarity-based algorithms, often referred to as memory-based collaborative filtering techniques, are one of the most successful methods in recommendation systems. When explicit ratings are available, similarity is usually defined using similarity functions, such as the Pearson correlation coefficient, cosine similarity or mean square difference. These metrics assume similarity is a symmetric criterion. Therefore, two users have equal impact on each other in recommending new items. In this paper, we introduce new weighting schemes that allow us to consider new features in finding similarities between users. These weighting schemes, first, transform symmetric similarity to asymmetric similarity by considering the number of ratings given by users on non-common items. Second, they take into account the habit effects of users are regarded on rating items by measuring the proximity of the number of repetitions for each rate on common rated items. Experiments on two datasets were implemented and compared to other similarity measures. The results show that adding weighted schemes to traditional similarity measures significantly improve the results obtained from traditional similarity measures.

An Intersection-based QoS Routing in Vehicular Ad Hoc Networks

Abstract: Vehicular Ad hoc Networks (VANET) face many challenging issues because of the rapid topology changes, frequent network partitions, and complicated urban environments. These special VANET characteristics seriously deteriorate the routing performance. In this paper, we propose a new vehicular routing protocol called Intersection based Routing with QoS support in VANET (IRQV). Based on Ant Colony Optimization (ACO), IRQV mainly consists of three processes, 1) terminal intersection selection process, 2) network exploration process, which is implemented using the QoS of local road segment and global end-to-end intersections, and 3) optimal routing path selection process. When initiating data packets forwarding session, IRQV dynamically chooses the optimal next intersection using latest routing information and adopts a simple greedy carry-and-forward mechanism to forward data between two adjacent intersections. In addition, we propose connectivity and transmission delay mathematical models for a 2-lane road segment scenario to estimate local QoS. Simulation results validate our derived road segment connectivity and transmission delay models, and show the effectiveness of IRQV compared with two geographical routing protocols in terms of delay, packet delivery ratio and overhead.

QoS-Aware Data Dissemination for Dense Urban Regions in Vehicular Ad Hoc Networks

Abstract: With an evolution of 5G and related technologies, there is a need of high data rate transfer between different communication objects such as vehicles, sensor nodes, or mesh clients connected to the Internet to maintain Quality of Service (QoS) at various levels. As vehicles in Vehicular Ad Hoc Networks (VANETs) are mainly used for safety related applications, so there is a need of an efficient QoS-aware data dissemination for various applications in different regions especially in dense urban regions where congestion is one of the major issues. Hence, to address this issue, in this paper, we propose a new mechanism to maintain QoS for data dissemination among the different vehicles in VANETs. An intelligent forwarding mechanism is used by newly defined metric which assigns weights to the different routing paths from source to destination. Separate algorithms are designed for route construction, and maintenance in the proposed scheme. The performance of the proposed scheme is studied by extensive simulations with respect to various metrics such as delay incurred, percentage of active links, and load on the network. The results obtained show that the proposed scheme is better than the other state-of-the-art existing schemes in the literature.

Frame-Based Medium Access Control for 5G Wireless Networks

Abstract: Millimeter wave (mmWave) communications is one of the key technologies for future 5th generation (5G) wireless networks. In this paper, we investigate the problem of medium access control (MAC) in mmWave networks. We develop a frame-based scheduling directional MAC protocol, termed FDMAC, to achieve the goal of leveraging collision-free concurrent transmissions to fully exploit spatial reuse in mmWave networks. The high efficiency of FDMAC is achieved by amortizing the scheduling overhead over multiple concurrent, back-to-back transmissions in a row. The core of FDMAC is a graph coloring-based scheduling algorithm, termed greedy coloring (GC) algorithm, that can compute near-optimal schedules with respect to the total transmission time with low complexity. FDMAC is analyzed and evaluated with simulations.

A Novel Energy-Saving One-Sided Synchronous Two-Way Ranging Algorithm for Vehicular Positioning

Abstract: As a result of the imprecise positioning accuracy, the satellite-based positioning system cannot offer the reliable and continuous positioning service for vehicular active safety application or vehicle monitoring in urban center with dense buildings or underground. With the advent of Vehicle Ad hoc Network (VANET), the Roadside Unit (RSU) can be considered as an anchor or base station to offer positioning reference. The ground-based positioning solution can help us acquire more precise position information through many times interaction, but multiple communications will result in heavy burden for network and more energy consumption. In this paper, we firstly analyze the pros and cons of representative algorithm, i.e., Symmetric Double Side-Two way Ranging (SDS-TWR). Then, we propose a novel energy-saving One-Sided Synchronous Two-Way Ranging (OSS-TWR) algorithm to reduce the communication times, which gains lower energy consumption and better performance than SDS-TWR. The experiments verify the validity of our solution. Finally, we make a conclusion and discuss the future works of vehicular positioning.

The Cognitive Internet of Things: A Unified Perspective

Abstract: In this article, we present a unified perspective on the cognitive internet of things (CIoT) It is noted that within the CIoT design we observe the convergence of energy harvesting, cognitive spectrum access and mobile cloud computing technologies We unify these distinct technologies into a CIoT architecture which provides a flexible, dynamic, scalable and robust network design road-map for large scale IoT deployment Since the prime objective of the CIoT network is to ensure connectivity between things, we identify key metrics which characterize the network design space We revisit the definition of cognition in the context of IoT networks and argue that both the energy efficiency and the spectrum efficiency are key design constraints To this end, we define a new performance metric called the `overall link success probability' which encapsulates these constraints The overall link success probability is characterized by both the self-sustainablitiy of the link through energy harvesting and the availability of spectrum for transmissions With the help of a reference scenario, we demonstrate that well-known tools from stochastic geometry can be employed to investigate both the node and the network level performance In particular, the reference scenario considers a large scale deployment of a CIoT network empowered by solar energy harvesting deployed along with the centralized CIoT device coordinators It is assumed that CIoT network is underlaid with a cellular network, ie, CIoT nodes share spectrum with mobile users subject to a certain co-existence constraint Considering the dynamics of both energy harvesting and spectrum sharing, the overall link success probability is then quantified It is shown that both the self-sustainability of the link, and the availability of transmission opportunites, are coupled through a common parameter, ie, the node level transmit power Furthermore, provided the co-existence constraint is satisfied, the link level success in the presence of both the inter-network and intra-network interference is an increasing function of the transmit power We demonstrate that the overall link level success probability can be maximized by employing a certain optimal transmit power Characterization of such an optimal operational point is presented Finally, we highlight some of the future directions which can benefit from the analytical framework developed in this paper

Smart Traffic Light for Low Traffic Conditions

Abstract: This work presents a novel traffic device (LaNPro) that avoids the stop of vehicles at junctions under low traffic conditions. To the best of our knowledge, this is the first smart traffic light designed for low traffic conditions. LaNPro is a security solution to preserve the physical integrity of drivers in countries with high social discrepancy. The server-side of the solution is deployed as a module of a smart traffic light, and it senses the presence of vehicles along the road through input devices (radars, cameras, road sensors, wireless communication) to assign the right of way. While any smart traffic light is able to manage low traffic intersections, we argue that they are not specialized devices to perform such task, and thus they may lack important optimizations. The main aggregated value of our approach is the ability to handle low traffic conditions, and that involves several challenges. Results show that our proposal may ensure the non-stop crossing of intersections having an expected traffic volume equal or less than ? = 0.10 vehicles per second, assuming intersections composed of 2, 3, or 4 lanes, road segments 200 m long, intersections 10 m wide, and vehicles 5 m long traveling at an average speed of μ = 40 km/h with standard deviation ? = 4 km/h.

Hybrid Architecture Performance Analysis for Device-to-Device Communication in 5G Cellular Network

Abstract: A large number of new data consuming applications are emerging in the daily routines of mobile users. Device-to-Device (D2D) communication as a new paradigm is introduced to reduce the increasing traffic and offload it to the user equipment (UE). With the development of UE multi-radio interface, we first develop a new hybrid architecture concept for D2D communication. The architecture combines ISM 2.4G spectrum as the Out-Band mode using Bluetooth and Wifi-Direct with the cellular spectrum as the In-Band mode. Secondly, we design a scheme that forms the Out-Band cluster and makes the following periodic signaling interaction via the Bluetooth interface. Traffic is transferred via the Wifi-Direct interface inside the cluster but carried on the cellular spectrum among the clusters. Simulation results show that our proposal increases the system throughput, saves power consumption and prolongs the clusters lifetime.

Replication-Aware Data Dissemination for Vehicular Ad Hoc Networks using Location Determination

Abstract: Location determination is one of the most difficult tasks to be achieved in Vehicular Ad Hoc networks (VANETs), as the nodes change their positions quickly due to high velocity. So, data dissemination to the vehicles in presence of high node mobility is one of the challenging issues to be resolved. To address these issues, in this paper, we propose a new Replication-Aware Data Dissemination (RADD) scheme for VANETs by estimating the location of the nodes. Separate algorithms are designed for position estimation, accessing the message from the remote vehicles, and route the packets to the destination. Also, vehicles on the road are sparsely distributed in some regions, so finding an appropriate vehicle for replica placement is also difficult as it needs a specialized approach. To search the suitable vehicle for replica placement, Bloom filters are used using which searching becomes fast and improves the overall performance of the system. Moreover, passive RFID tags are used on the vehicles and the RFID readers are placed on the RSUs to collect the data from these tags. These tags and readers are used to determine the vehicles positions in short range communication where GPS system does not work well. Hence, in the proposed scheme, there is no need of placement of access points on the either side of the road which reduces the complexity of the message dissemination in the proposed scheme. The complexity analysis of the proposed scheme is evaluated in different network conditions with respect to data dissemination from source to destination. The performance of the proposed scheme was evaluated using different evaluation metrics in comparison to the other existing state-of-the-art schemes. The results obtained show that the proposed scheme performs better than the other existing schemes of its category with respect to various metrics. Specifically, there are improvements of 18 % in reliability, 27 % in replication cost, and 7 % in PDR with respect to the existing state-of-art protocols.

Controlling Cloud Data Access Based on Reputation

Abstract: Cloud computing offers a new way of service provision and will play an important role in the next generation mobile networks and services (in short 5G). Cloud data privacy and security protection is a crucial issue that impacts the success of cloud computing and may impede the development of 5G. Literature has proposed a number of cloud data access control schemes. However, existing solutions suffer from high computation complexity and cost and therefore few of them have been really deployed in practice. In this paper, we propose a practical scheme to securely access cloud data and effectively reduce access risk according to the reputations of cloud computing entities by applying proxy re-encryption in the situation that the data owner is not available online or does not know how to control the access. The advantages, security and performance of the proposed scheme are evaluated and justified through extensive analysis, security proof and implementation. The results show the efficiency and effectiveness of our scheme for practical deployment.

Interference Minimization in 5G Heterogeneous Networks

Abstract: In this paper, we focus on one of the representative 5G network scenarios, namely multi-tier heterogeneous cellular networks. User association is investigated in order to reduce the down-link co-channel interference. Firstly, in order to analyze the multi-tier heterogeneous cellular networks where the base stations in different tiers usually adopt different transmission powers, we propose a Transmission Power Normalization Model (TPNM), which is able to convert a multi-tier cellular network into a single-tier network, such that all base stations have the same normalized transmission power. Then using TPNM, the signal and interference received at any point in the complex multi-tier environment can be analyzed by considering the same point in the equivalent single-tier cellular network model, thus significantly simplifying the analysis. On this basis, we propose a new user association scheme in heterogeneous cellular networks, where the base station that leads to the smallest interference to other co-channel mobile stations is chosen from a set of candidate base stations that satisfy the quality-of-service (QoS) constraint for an intended mobile station. Numerical results show that the proposed user association scheme is able to significantly reduce the down-link interference compared with existing schemes while maintaining a reasonably good QoS.

Wireless Medium Access Control under Mobility and Bursty Traffic Assumptions in WSNs

Abstract: In Wireless Sensor Networks (WSNs) the nodes can be either static or mobile depending on the requirements of each application. During the design of Medium Access Control (MAC) protocols, mobility may pose many communication challenges. These difficulties require first a link establishment between mobile and static nodes, and then an energy efficient and low delay burst handling mechanism. In this study, we investigate preamble-sampling solutions that allow asynchronous operation. We first introduce anycast transmission to ContikiMAC where a mobile node emits an anycast data packet whose first acknowledging node will serve as responsible to forward it towards the sink. Once this link is established, burst transmission can start, according to the respective burst handling mechanism of ContikiMAC. Although it is considered as negligible in the literature, such an anycast-based on-the-fly operation actually results in high packet duplication at the sink. Hence, we demonstrate that even a basic anycast-based M-ContikiMAC would fail to handle bursty traffic from mobile nodes mainly due to increased unnecessary traffic and channel occupancy. We then propose Mobility-Enhanced ContikiMAC (ME-ContikiMAC), a protocol that reduces packet duplications in the network by more than 90 % comparing to M-ContikiMAC. Moreover, our results in a 48-node scenario show that ME-ContikiMAC outperforms a number of state-of-the-art solutions (including MoX-MAC and MOBINET), by terms of reducing both delay and energy consumption.

Software-Defined Wireless Transport Networks for Flexible Mobile Backhaul in 5G Systems

Abstract: Traditionally microwave backhaul has been configured and operated in a static manner by means of vendor specific management systems. This mode of operation will be difficult to adapt to the new challenges originated by 5G networks. New mechanisms for adaptation and flexibility are required also in this network segment. The usage of a signaled control plane solution (based on OpenFlow) will facilitate the operation and will provide means for automation of actions on the wireless transport network segment. In addition to that, a standard control plane helps to reach the multi-vendor approach reducing complexity and variety of current per-vendor operation. This paper presents the motivation for the introduction of programmability concepts in wireless transport networks and illustrate the applicability of such control plane with two relevant use cases for dynamically controlling wireless transport nodes in 5G networks. Extensions to OpenFlow protocol are also introduced for building Software Defined Wireless Transport Networks (SDWTNs).

A Green Approach for Selfish Misbehavior Detection in 802.11-Based Wireless Networks

Abstract: IEEE 802.11 is one of the most well-established and widely used standard for wireless LAN. Its Medium Access control (MAC) layer assumes that the devices adhere to the standard's rules and timers to assure fair access and sharing of the medium. However, wireless cards driver flexibility and configurability make it possible for selfish misbehaving nodes to take advantages over the other well-behaving nodes. The existence of selfish nodes degrades the QoS for the other devices in the network and may increase their energy consumption. In this paper we propose a green solution for selfish misbehavior detection in IEEE 802.11-based wireless networks. The proposed scheme works in two phases: Global phase which detects whether the network contains selfish nodes or not, and Local phase which identifies which node or nodes within the network are selfish. Usually, the network must be frequently examined for selfish nodes during its operation since any node may act selfishly. Our solution is green in the sense that it saves the network resources as it avoids wasting the nodes energy by examining all the individual nodes of being selfish when it is not necessary. The proposed detection algorithm is evaluated using extensive OPNET simulations. The results show that the Global network metric clearly indicates the existence of a selfish node while the Local nodes metric successfully identified the selfish node(s). We also provide mathematical analysis for the selfish misbehaving and derived formulas for the successful channel access probability.

Adaptive SON and Cognitive Smart LPN for 5G Heterogeneous Networks

Abstract: To overcome the challenge of large data demanding in future 5G cellular networks, heterogeneous networks (HetNets) take advantage of low power nodes (LPNs) to enhance capacity and coverage. This paper aims at 5G HetNets and presents a novel scheme of adaptive self-organization network (SON) by integrating cognitive radio (CR) with inter-cell interference coordination (ICIC). Particularly, we combine the spectrum sensing function from CR and the radio resource layering function from ICIC. Our work addresses the issues of smart low-power node (SLPN) development, which associates appropriate sectorization with radio resource allocation during the self-organization process. We further develop a Hungarian algorithm based self-organization strategy to improve the SLPN adaptive optimization. Simulation results show that our proposed scheme can achieve considerable gain in terms of throughput and coverage, with extra rewards of high flexibility and low complexity in HetNet SON.

Service-Oriented Virtual Machine Placement Optimization for Green Data Center

Abstract: The first service-oriented virtual machine (VM) placement for green data center is designed in this work. Integer Linear Programming (ILP) is the problem design basis. The Tree algorithm is proposed to place VM role instances at the lowest communication cost, economizing the construction cost with fewer physical servers. Another Forest algorithm is also proposed for balancing the computation load between the physical machines. Both of the proposed algorithms are formulated on the graph theoretic technique and evaluated and analyzed using the Best Fit algorithm in the simulations. Although the total power consumption and average utility of both proposed algorithms are slightly impaired, the unnecessary outbound communication cost is significantly eliminated and decreased, especially in the immense number of services. The results show that the proposed Tree and Forest algorithms provide lower communication cost than the Best Fit algorithm, and achieve green communications for large scale environment such as cloud or green data center.

Self-Organizing Scheme Based on NFV and SDN Architecture for Future Heterogeneous Networks

Abstract: Future cellular networks will be of high capacity and heterogeneity. The structure and architecture will require high efficiency and scalability in network operation and management. In this paper, we address main requirements and challenges of future cellular networks and introduce network function virtualisation (NFV) with software defined networking (SDN) to realize the self-organizing (SO) scheme. NFV integrates the hardware appliances together in industry standard servers. And SDN performs as core controller of the network. The proposed SO scheme is based on soft fractional frequency reuse (SFFR) framework. The scheme takes different traffic demands into consideration and allocates the power adaptively. Finally the system is proved to be more scalable, energy-saving, and intelligent.

Integrating WMN Based Mobile Backhaul with SDN Control

Abstract: Resilient high capacity and low delay millimeter wave wireless mesh networks (WMNs) can provide suitable backhaul connections for future broadband mobile networks. The WMN solution is best suited in cases where base stations are installed in locations without optical fiber connection to transport network, e.g., small-cell deployment to hot spots in dense urban areas. Recently software defined network (SDN) concept has become popular in many networking areas including mobile networks. One of the key promises is to provide an efficient way for network operators to extend and create new services. As the whole network is controlled by a single central entity that is based on software code, it would be easy to make large scale network upgrades without need to wait that updates are available for all network elements (NEs). There is, however, a clear conflict between SDN ideas and WMN operation. The performance and reliability of the latter one is heavily depended on fast local reactions to, e.g., link degradations. Centralized control would introduce longer delays in reactions. In this paper, we are proposing a concept which solves these problems and allows for combining the best features of both WMN and SDN.

Periodic Query Optimization Leveraging Popularity-Based Caching in Wireless Sensor Networks for Industrial IoT Applications

Abstract: With the rapid development of the Internet of Things (IoT), billions of smart devices should be available for sensing environment variables and reporting events periodically that may happen in certain regions, for supporting industrial applications. It is usual that contiguous queries on point-of-interests may have some region overlapping. In this setting, sensory data retrieved by recent queries may be beneficial for answering the queries forthcoming, when these data are fresh enough. To address this challenge, we propose a popularity-based caching strategy for optimizing periodic query processing. Specifically, the network region is divided using a cell-based manner, where each grid cell is abstracted as an elementary unit for the caching purpose. Fresh sensory data are cached in the memory of the sink node. The popularity of grid cells are calculated leveraging the queries conducted in recent time slots, which reflects the possibility that grid cells may be covered by the queries forthcoming. Prefetching may be performed for grid cells with a higher degree of popularity when missed in the cache. These cached sensory data are used for facilitating the query answering afterwards. The simulation results show that our approach can reduce the communication cost significantly and increase the network capability.

An Intelligent Context-aware Congestion Resolution Protocol for Data Dissemination in Vehicular Ad Hoc Networks

Abstract: With high velocity, and sparse distribution of vehicles on the road, routing a packet to its destination is one of the major challenges in Vehicular Ad Hoc Networks (VANETs). To reduce the complexity of transmissions, only context-aware data is required for successful transfer of alerts to the passengers as unnecessary information may cause a performance bottleneck at some point in VANETs. To address this issue, in this paper, we propose a new context-aware congestion resolution protocol called as-minimum calculated desired time (MCDT) for Intelligent Data Dissemination in VANETs. In the proposed scheme, first the link stability is computed and then, a peak stable zone is constructed which is used to estimate the virtual connectivity of the nodes. A module for recovery of lost link using minimum angle method is also proposed. The proposed scheme can be used for vast industrial applications, where there is a need of contextual-aware information dissemination with less delay, and higher accuracy. The proposed scheme is evaluated in different network scenarios by varying the parameters such as velocity, and density of the vehicles. The results obtained yield an improvement of more than 90 % in end-to-end delay (E2ED), 11.75 % in download speed, 7 % enhanced resource utilization, and a decrease of 16 % in overhead in the proposed scheme as compared to other state-of-the-art existing schemes.

An Efficient RFID Search Protocol Based On Clouds

Abstract: In RFID applications, we may have to search a number of particular goods in a large-scale number of products. Previous work solve this problem to some extent. Firstly, they cannot work when the cardinality of X is lager than Y. Besides, they assume the reader has a powerful capacity which is adequate for computation. In this paper, we propose ITSP --- Iterative Tag Search Protocol based on cloud which solves these two problems. It uses multi-rounds communication on behalf of one-round communication to make search work when |X| > |Y|. Besides the readers request cloud service to help do computation to make up its limited computation capacity. Further, we still study the security during RFID Search. To be secure, ITSP authenticates readers and tags in advance to keep secure. Experimental results show that proposed scheme achieves higher searching efficiency with the improvement at least 19 %.