Showing papers in "Telecommunication Systems in 2016"

A survey on position-based routing for vehicular ad hoc networks

Abstract: Position-based routing is considered to be a very promising routing strategy for communication within vehicular ad hoc networks (VANETs), due to the fact that vehicular nodes can obtain position information from onboard global positioning system receivers and acquire global road layout information from an onboard digital map. Position-based routing protocols, which are based mostly on greedy forwarding, are well-suited to the highly dynamic and rapid-changing network topology of VANETs. In this paper, we outline the background and the latest development in VANETs and survey the state-of-the-art routing protocols previously used in VANETs. We present the pros and cons for each routing protocol, and make a detailed comparison. We also discuss open issues, challenges and future research directions. It is observed that a hybrid routing protocol is the best choice for VANETs in both urban and highway environments.

A multicast delivery approach with minimum energy consumption for wireless multi-hop networks

Abstract: Multicast delivery in wireless multi-hop networks has become the popular research topic and holds the important applications such as sensor and tactical networks. However, how to minimize multicast energy consumption and prolong the lifetime of multicast connection in wireless multi-hop networks with limited energy is a challenge at present. This paper presents a new approach to solve this problem by considering the cognitive ability of nodes. Above all, we exploit the directional reception antennas to propose a directional reception two-step reconstruction routing scheme to set up multicast tree for wireless multi-hop networks. Different from previous methods, we grant the cognitive ability to each node so that they can obtain the minimum transmission power by sensing, learning, acting, and deciding. We propose two algorithms to find the minimum transmission power of all the nodes in the multicast tree built above. And a global optimal multicast delivery algorithm with the minimum energy consumption is proposed to implement effective multicast communication for wireless multi-hop networks with energy limited. Numerical experiments show that the proposed approach can significantly improve the multicast performance of wireless multi-hop networks with energy limited such as the lifetime of multicast connection and transmission power.

Improvements of DV-Hop localization algorithm for wireless sensor networks

Abstract: Based on the improvements of the original DV-Hop localization algorithm, three new localization algorithms (iDV-Hop1, iDV-Hop2, and Quad DV-Hop) are presented in this article. In iDV-Hop1 and iDV-Hop2, all steps of the original DV-Hop are kept, and several steps based on geometry improvements of the localization problem are added in order to obtain better localization accuracy. The third algorithm (Quad DV-Hop) formulated the localization problem as bounded least squares problem, to be solved by quadratic programming. Simulations are carried out on the four different types of network topology by varying nodes communication range, number of anchor nodes and number of nodes. Comparison of our algorithms with the original DV-Hop and Improved DV-Hop algorithms are given. It is shown that iDV-Hop1 algorithm can significantly reduce the localization error (up to three times) in scenarios with irregular topologies compared to DV-Hop and Improved DV-Hop. In scenarios with regular topologies, iDV-Hop2 and Quad DV-Hop showed better performance compared to DV-Hop and Improved DV-Hop (up to 11 % lower localization error).

A comparative analysis of energy conservation approaches in hybrid wireless sensor networks data collection protocols

Abstract: Wireless sensor network (WSN) has become part of human life as it is used in several applications including healthcare, environment and agricultural, public safety, military, transportation as well as in the industry. In spite of its usefulness, it is challenging to maintain long-term operations due to limited battery life. Several energy efficient protocols have been designed to prolong the network lifetime. The integration of mobility technology with the conventional static sensor network, described as hybrid WSN, promises a new solution that balances energy consumption among sensor nodes and extends the network lifetime. To the best of our knowledge, there has not been as yet an evaluation of the energy-efficiency of the data collection approaches in terms of the energy conservation techniques adopted. In this paper, the architecture of data collection approaches in WSN is discussed. Then, we propose and discuss a taxonomy of types of data collection in WSN. We further present and discuss in details a thematic taxonomy of energy conservation techniques adopted in the various hybrid WSN data collection approaches. Consequently, we compare the different energy conservation approaches that minimize energy consumption in hybrid WSN, highlighting their pros and cons. In conclusion, we point out open research challenges and future directions in the field.

Secure and efficient data transmission in the Internet of Things

Abstract: Recently, the concept of the Internet of Things (IoT) has drawn considerable attention from both industry and academia. In the IoT, millions of objects with sensors collect data and send the data to servers that analyze, manage and use the data in order to construct some kinds of smart systems, such as smart grid, intelligent transportation systems, healthcare systems and even smart city. It is critical to establish a secure channel between the sensors and servers in order to ensure the correctness of collected data. If the collected data is tampered, the results of data analysis is unbelievable, and may even bring serious disaster. In this paper, we propose a heterogeneous ring signcryption scheme for secure communication from sensors to servers. We prove that this scheme has the indistinguishability against adaptive chosen ciphertext attacks (IND-CCA2) and existential unforgeability against adaptive chosen messages attacks under the computational Diffie---Hellman problem in the random oracle model. Our scheme has the following advantages (1) it simultaneously achieves confidentiality, integrity, authentication, non-repudiation and anonymity in a logical single step; (2) it is heterogeneous and allows a sensor node in an identity-based cryptography to send a message to a server in a public key infrastructure. These features make our scheme suitable for data transmission in the IoT.

Impact of packet loss and delay variation on the quality of real-time video streaming

Abstract: The aim of this work is to bring complex view on video streaming service performance within IP-based networks. Video quality as a part of multimedia technology has a crucial role nowadays due to this increase. Since architecture of IP network has not been designed for real-time services like audio or video, there are many factors that can influence the final quality of service, especially packet loss and delay variation (also known as Jitter). The research was focused on the quality of video data delivery in many scenarios included different packet loss rate and simulating of different delay variation values in the network. Performed tests were evaluated by using of video objective methods. Based on results of these measurements, an extended QoS model for estimation of triple play services was designed. The proposed model allows us to compute the estimated objective quality parameters that describe the final quality of video service as a part of triple play services.

A context-aware search system for Internet of Things based on hierarchical context model

Abstract: In recent years, numerous sensing devices and wireless networks are immersed into our living environments, creating the Internet of Things (IoT) integrating the cyber and physical objects. Searching for objects in IoT is a challenging problem because the context relationships among IoT objects are various and complex. The traditional web search approaches cannot work well in the IoT search domain because they miss the critical characteristics of the context relationships. In addition, a user's dynamic and changing context affects the user's information needs, and an IoT search system should exploit context relationship in IoT for retrieving relevant information suitable for the user's current context. In this paper, we present a context-aware search system for IoT, which aims to search objects and related information with more suitable results. We construct a hierarchical context model based on ontology to represent the IoT objects and their contextual relationships. Then, searches are executed with consideration of users' context that is recognized by a context-aware hidden Markov model. Experimental results confirmed that users could obtain more suitable and reasonable search results than with a typical web or map search system.

An optimization-based robust routing algorithm to energy-efficient networks for cloud computing

Abstract: This paper studies the routing problem in energy-efficient networks for cloud computing. We propose a robust routing algorithm to reach the higher network energy efficiency, which is based on optimization problem. To attain the highly energy-efficient routing in energy-efficient networks for cloud computing, the link of low utilization is turned into the sleeping state to save the network energy. At the same time, the low link traffic is aggregated to the link with high utilization to enhance the link utilization and to sleep the links as many as possible. We present an optimized link sleeping method to maximize the number of the sleeping links. By targeting the network robustness, a weight adaptive strategy is brought forth to reduce the link congestion and enhance the robustness of the network. Simulation results indicate that our algorithm is effective and feasible to achieve energy-efficient networks for cloud computing.

Energy-aware two-way relaying networks under imperfect hardware: optimal throughput design and analysis

Abstract: In this paper, we propose a new formula for achieving optimal throughput in energy-aware cooperative networks with generic time and power energy harvesting protocol, namely time power switching based relaying (TPSR). Especially, this investigation analyzes the impact of imperfect hardware at the relay node and the destination node in the two-way relaying networks (TWRN). This analysis enables us to derive the closed-form expressions of outage probabilities of signal-to-noise and distortion ratio (SNDR) at the destination nodes under the effect of hardware impairments. Interestingly, the optimal policy of joint wireless information and energy transfer is designed to maximize the system throughput by finding the optimal time switching and power splitting fractions in the proposed TPSR protocol. An important achievement is that the proposed optimal design offers the maximum throughput of system when we consider the trade-off between throughput and time-power factors in energy harvesting protocol by both numerical method and simulation. Numerical results provide practical insights into the performance of energy-aware TWRN under hardware impairments. Monte-Carlo method is also deployed to corroborate the accuracy of analytical derived expressions.

A trust aware routing protocol for energy constrained wireless sensor network

Abstract: The reliable data delivery is a challenging task in Wireless Sensor Networks (WSNs) due to dynamic and unpredictable changing behaviors of nodes. The traditional cryptographic and authentication based schemes can't be adopted due to their associated cost and incapability to counter nodes misbehavior attacks. Recently, trust based solutions have proved to be more effective to address nodes' misbehavior attacks. Apart from isolating misbehaving nodes, the existing trust based schemes lacks the capability to minimize link failure notifications due to transient transmission disruption which consequently give rise to frequent route breakages thereby undermining throughput and route stability. Moreover, the existing solutions give rise to high energy consumption and control overhead in pursuit of trust estimation and network-wide dissemination which not only adds to network congestion but also undermines network lifetime. In this paper, we present a Trust and Energy aware Routing Protocol (TERP) that makes use of a distributed trust model for the detection and isolation of misbehaving nodes. TERP incorporates a composite routing function that encompasses trust, residual-energy, and hop count of neighbor nodes in making routing decisions. This multi-facet routing strategy helps to balance out energy consumption among trusted nodes while routing data using shorter paths. Moreover, TERP intelligently evaluates the actual link breakage thereby avoiding unnecessary route discoveries. Simulation results demonstrate improved throughput, network lifetime and route stability of TERP when compared to existing work.

Traffic aware routing in vehicular ad hoc networks: characteristics and challenges

Abstract: Vehicular ad hoc networks (VANETs) are gaining tremendous interest among researchers and industries. Although the main reason for developing VANETs is traffic safety, many applications such as traffic status monitoring, road traffic management, routing and distribution of data, have emerged. VANETs exploit multi-hop communications among vehicles to deliver data packets. However, with fast mobility and intermittent link connectivity between vehicles, efficient and reliable routing in VANETs is becoming a challenging task. In order to make routing protocols robust to frequent communication disruptions and aware of unstable traffic and network conditions, several new routing metrics have been integrated with routing protocols. Such protocols are called traffic aware routing (TAR) protocols as their routing decisions are influenced by traffic and network status. The goal of this paper is to review the most recent traffic aware routing protocols while emphasising on traffic and network conditions awareness issues. In addition, this review investigated TAR protocols capabilities and limitations in terms of routing process, routing metrics measurement, forwarding mechanisms and recovery techniques. Moreover, challenges, critical issues and open research problems were discussed in the "Challenges and issues to consider" sections.

AMOF: adaptive multi-objective optimization framework for coverage and topology control in heterogeneous wireless sensor networks

Abstract: In this paper, we propose adaptive multi-objective optimization framework based on non-dominated sorting genetic algorithm-II and learning automata (LA) for coverage and topology control in heterogeneous wireless sensor networks. The multi-objective optimization approach of the proposed framework, called MOOCTC (multi-objective optimization coverage and topology control), can simultaneously optimize several conflicting issues such as number of active sensor nodes, coverage rate of the monitoring area and balanced energy consumption while maintaining the network connectivity. This approach incorporates problem-specific knowledge in its operators to find high-quality solutions. In addition, this approach uses LA to dynamically adapt the crossover and mutation rates without any external control to improve the behavior of the optimization algorithm. Simulation results demonstrate the efficiency of the proposed multi-objective optimization approach in terms of lifetime, coverage and connectivity.

A locality-based range-free localization algorithm for anisotropic wireless sensor networks

Abstract: Location discovery is one of the fundamental services in Internet of things built with wireless sensor networks (WSNs). In this paper, we propose AnSuper, a novel range-free localization algorithm that provides accurate location estimates in anisotropic WSNs. In AnSuper, every anchor first selects a set of friendly anchors to which its distance estimates can be accurately obtained. These anchors are then broadcasted to neighboring common nodes, with which they can obtain accurate distance estimates to the anchors by using a novel locality-based algorithm and consequently calculate their positions. We discuss how to suppress error accumulation in the localization process. AnSuper can handle multiple anisotropy factors, including uneven nodal distribution and irregularity of the deployment region. Simulation results show that, compared with state-of-the-art solutions, AnSuper improves localization accuracy by more then 30 %.

A generic buffer occupancy expression for stop-and-wait hybrid automatic repeat request protocol over unstable channels

Abstract: Recently, there has been a rapid progress in the field of wireless networks and mobile communications which makes the constraints on the used links clearly unconcealed. Wireless links are characterized by limited bandwidth and high latencies. Moreover, the bit-error-rate (BER) is very high in such environments for various reasons out of which weather conditions, cross-link interference, and mobility. High BER causes corruption in the data being transmitted over these channels. Therefore, convolutional encoding has been originated to be a professional means of communication over noisy environments. Sequential decoding, a category of convolutional codes, represents an efficient error detection and correction mechanism which attracts the attention for most of current researchers as for having a complexity that is dependent to the channel condition. In this paper, we propose a new queuing study over networking systems that make use of sequential decoders. Hence, the adopted flow and error control refer to stop-and-wait hybrid automatic repeat request. However, our queuing study is a novel extension to our prior work in which the lowest decoding complexity was fixed and did not account for the channel state. In other words, our proposed closed-form expression of the average buffer occupancy is totally generic and parameterized by not only channel condition and packet incoming rate, but also those that are automatically adapted to the channel conditions which include lower and upper bound decoding limits.

Implementation of call admission control technique in HAP for enhanced QoS in wireless network deployment

Abstract: Exponential growth in the number of subscribers of mobile communication services has prompted service providers to maintain high level of quality of service (QoS). QoS performance is usually measured in terms of the probability of call blocking and probability of call dropping parameters. Recently, high altitude platform (HAP) is being explored to deploy mobile communication services due to various advantages. In this paper, a modified call admission control (CAC) technique has been proposed. We propose a novel CAC technique which uses two schemes viz. "bandwidth reservation" and "degradation scheme" to deliver the desired QoS. Under the `bandwidth reservation scheme', we allocated dedicated bandwidth to each category of service. Consequently, when a new call request arrives and when there are no more channels available, in that particular class; we use the `adaptive degradation scheme' under which the allocated bandwidth of each channel is reduced slightly and additional channels are created and hence allocated to the new call request. Using these schemes in conjunction with CAC, better bandwidth utilization has been obtained over preferred category of committed QoS and the connections services enjoy more available bandwidth with improve in the blocking probability and dropping probability.

Blocking probabilities of elastic and adaptive calls in the Erlang multirate loss model under the threshold policy

Abstract: In this paper, we propose a new multirate teletraffic loss model of a single link with certain bandwidth capacity that accommodates Poisson arriving calls, which can tolerate bandwidth compression, under the threshold policy of admission control. When compression occurs, the service time may increase (elastic calls) or not (adaptive calls). The threshold policy can provide different QoS among service-classes by limiting the number of calls of a service-class up to a predefined threshold, which can be different for each service-class. The proposed model does not have a product form solution for the determination of the steady state probabilities. However, we approximate the model by a reversible Markov chain, and provide recursive formulas for the efficient calculation of the call-level performance metrics, such as call blocking probabilities and link utilization. In addition, we provide similar formulas when the threshold policy co-exists with the bandwidth reservation policy. The latter reserves part of the available link bandwidth to benefit calls of high bandwidth requirements. The accuracy of the proposed formulas is verified through simulation and found to be quite satisfactory. We also show the necessity and consistency of the proposed models.

Probabilistic Model for M2M in IoT networking and communication

Abstract: In this paper, a probabilistic model for M2M in IoT networking and communication mode is presented with mobile and dynamic machines in the network. The scenario is considered stochastic and thus probability distribution describing the times between successive machines entry in to the network is predicted by means of a graph. A graph based model is also presented to find the shortest path and lowest cost between machines. For large scale network, parallel M2M establish connection inside a network and are partitioned and dynamically refigured such as IoT. Simulation were performed for multiple M2M array for different state, timing and power consumption along with the scheduling scheme are considered.

Intersection-based forwarding protocol for vehicular ad hoc networks

Abstract: Vehicular ad hoc networks (VANETs) make the transmission between vehicles possible without infrastructure. However, ad hoc networks also increase the redundancy of networks. To decrease the redundancy of networks and make VANETs more efficient, we introduce the new routing protocol: intersection-based forwarding protocol (IBFP). In urban-area, we set virtual ports (VP) at each intersection. The virtual port is served by stopping vehicle which is waiting for the traffic light in front of the intersection. VP will gather all the packets that need to be forwarded from all passing by vehicles. When VP leaves this intersection, it will transmit all the copies of packets to the next VP. As the movement of VP, packets can be transmitted to every intersection in a very short period of time like the epidemic process. Destination vehicles can receive packets with high success rate. The epidemic process only exists among VPs. Therefore, on the premise of high success rate, the proposed IBFP can transmit packets with less delay and redundancy.

EMIP: energy-efficient itinerary planning for multiple mobile agents in wireless sensor network

Abstract: As software entities that migrate among nodes, mobile agents (MAs) are able to deliver and execute codes for flexible application re-tasking, local processing, and collaborative signal and information processing. In contrast to the conventional wireless sensor network operations based on the client---server computing model, recent research has shown the efficiency of agent-based data collection and aggregation in collaborative and ubiquitous environments. In this paper, we consider the problem of calculating multiple itineraries for MAs to visit source nodes in parallel. Our algorithm iteratively partitions a directional sector zone where the source nodes are included in an itinerary. The length of an itinerary is controlled by the angle of the directional sector zone in such a way that near-optimal routes for MAs can be obtained by selecting the angle efficiently in an adaptive fashion. Simulation results confirm the effectiveness of the proposed algorithm as well as its performance gain over alternative approaches.

A new meta-heuristic ebb-tide-fish-inspired algorithm for traffic navigation

Abstract: More and more bio-inspired or meta-heuristic algorithms have been proposed to tackle the tough optimization problems. They all aim for tolerable velocity of convergence, a better precision, robustness, and performance. In this paper, we proposed a new algorithm, ebb tide fish algorithm (ETFA), which mainly focus on using simple but useful update scheme to evolve different solutions to achieve the global optima in the related tough optimization problem rather than PSO-like velocity parameter to achieve diversity at the expenses of slow convergence rate. The proposed ETFA achieves intensification and diversification in a new way. First, a flag is used to demonstrate the search status of each particle candidate. Second, the single search mode and population search mode tackle the intensification and diversification for tough optimization problem respectively. We also compare the proposed algorithm with other existing algorithms, including bat algorithm, cat swarm optimization, harmony search algorithm and particle swarm optimization. Simulation results demonstrate that the proposed ebb tide fish algorithm not only obtains a better precision but also gets a better convergence rate. Finally, the proposed algorithm is used in the application of vehicle route optimization in Intelligent Transportation Systems (ITS). Experiment results show that the proposed scheme also can be well performed for vehicle navigation with a better performance of the reduction of gasoline consumption than the shortest path algorithm (Dijkstra Algorithm) and A* algorithm.

A streaming flow-based technique for traffic classification applied to 12 + 1 years of Internet traffic

Abstract: The continuous evolution of Internet traffic and its applications makes the classification of network traffic a topic far from being completely solved. An essential problem in this field is that most of proposed techniques in the literature are based on a static view of the network traffic (i.e., they build a model or a set of patterns from a static, invariable dataset). However, very little work has addressed the practical limitations that arise when facing a more realistic scenario with an infinite, continuously evolving stream of network traffic flows. In this paper, we propose a streaming flow-based classification solution based on Hoeffding Adaptive Tree, a machine learning technique specifically designed for evolving data streams. The main novelty of our proposal is that it is able to automatically adapt to the continuous evolution of the network traffic without storing any traffic data. We apply our solution to a 12 + 1 year-long dataset from a transit link in Japan, and show that it can sustain a very high accuracy over the years, with significantly less cost and complexity than existing alternatives based on static learning algorithms, such as C4.5.

Field measurements for practical unlicensed communication in the UHF band

Abstract: This paper presents the result of a measurement campaign conducted in Italy, Spain, and Romania to obtain empirical values for the parameters upon which unlicensed devices could distinguish in a hidden node scenario between empty and occupied TV channels. Signal power measurements in the UHF frequency band (470---860 MHz) have been carried out on rural, sub-urban, and urban sites, at different heights over the ground by using different analysis bandwidths. The results have been analyzed with respect to the hidden node margin problem, spectrum sensing bandwidth, and occupancy threshold, to produce a set of practical parameters upon which harmless unlicensed communication in the UHF TV bands is feasible.

Recharging versus replacing sensor nodes using mobile robots for network maintenance

Abstract: Wireless sensor networks (WSNs) have been of very high interest for the research community for years, but the quest for deploying a self-sustained network and effectively prolonging its lifetime has not found a satisfactory answer yet. Two main approaches can be identified that target this objective: either "recharging" or "replacing" the sensor nodes that are running out of energy. Of particular interest are solutions where mobile robots are used to execute the above mentioned tasks to automatically and autonomously maintain the WSN, thus reducing human intervention. Recently, the progress in wireless power transfer techniques has boosted research activities in the direction of battery recharging, with high expectations for its application to WSNs. Similarly, also sensor replacement techniques have been widely studied as a means to provide service continuity in the network. The objective of this paper is to investigate the limitations and the advantages of these two research directions. Key decision points must be identified for effectively supporting WSN self-maintenance: (i) which sensor nodes have to be recharged/replaced; (ii) in which order the mobile robot is serving (i.e., recharging/replacing) the nodes and by following which path; (iii) how much energy is delivered to a sensor when recharged. The influence that a set of parameters, relative to both the sensors and the mobile robot, has on the decisions will be considered. Centralized and distributed solutions are compared in terms of effectiveness in prolonging the network lifetime and in allowing network self-sustainability. The performance evaluation in a variety of scenarios and network settings offers the opportunity to draw conclusions and to discuss the boundaries for one technique being preferable to the other.

SDAW: secure data aggregation watermarking-based scheme in homogeneous WSNs

Abstract: Redundant data retransmission problem in wireless sensor networks (WSNs) can be eliminated using the data aggregation process which combines similar data to reduce the resource-consumption and consequently, saves energy during data transmission. In the recent days, many researchers have focused on securing this paradigm despite the constraints it imposes such as the limited resources. Most of the solutions proposed to secure the data aggregation process in WSNs are essentially based on the use of encryption keys to protect data during their transmission in the network. Indeed, the key generation and distribution mechanisms involve additional computation costs and consume more of energy. Considering this, in this paper, we propose a new security mechanism to secure data aggregation in WSNs called SDAW (secure data aggregation watermarking-based scheme in homogeneous WSNs). Our mechanism aims to secure the data aggregation process while saving energy. For this, the mechanism uses a lightweight fragile watermarking technique without encryption to insure the authentication and the integrity of the sensed data while saving the energy. The links between the sensor nodes and the aggregation nodes, and also the links between the aggregation nodes and the base station are secured by using the watermarking mechanism.

Intelligent selection of threshold in cognitive radio system

Abstract: To evaluate the performance of cognitive radio (CR) under the energy detection scheme, the proper selection of threshold is an important and a critical task. The threshold is generally selected, either under a target probability of detection $$(\overline{P_d})$$(Pd¯) called as the constant detection rate (CDR) principle, or under the target probability of false alarm $$(\overline{P_{fa}})$$(Pfa¯), called as the constant false alarm rate (CFAR) principle. To ensure sufficient protection to the licensed users (or primary users), the selection of threshold under the CDR principle is best suited. This paper discusses and analyzes the inefficiency of CR under the blind use of CDR principle, mainly, when primary receiver is located at a sufficient distance d from the secondary transmitter where signal to interference plus noise ratio (SINR) is larger than a cut-off value $$SINR_{th}$$SINRth (which is a minimum SINR required to properly decode the intended information of primary user). To overcome this inefficiency, we propose an approach which while considering distance d between the secondary transmitter and primary receiver as an important parameter, makes an interference-aware selection of threshold based on the CDR and CFAR principles. Under the proposed approach, the CR system achieves a significant gain in its throughput even under the low signal to noise ratio conditions.

Prolonging the lifetime of wireless sensor networks using secondary sink nodes

Abstract: This work proposes an approach for improving energy-efficiency and thus increasing network lifetime in wireless sensor network (WSN) using a logical energy tree (LET). In our scheme, LET is constructed using the remaining available energy in each node. Two routing algorithms are framed based on LET: one with centralized sink node called LETCSN and the other with centralized sink node and secondary sink nodes called LETSSN. sensor nodes are deployed in some fixed patterns. A mathematical model is devised to understand the effect of node deployment pattern on improving network lifetime. Both proposed routing algorithms are evaluated with seven different deployment patterns, simulated in ns-2 and are compared with the existing classic algorithms based on the number of data packets, throughput, network lifetime, and data packet's average network lifetime product. Our evaluation and simulation results show that LETSSN maximizes the network lifetime for all node-deployment patterns taken into consideration.

Traffic differentiation and dynamic duty cycle adaptation in IEEE 802.15.4 beacon enabled WSN for real-time applications

Abstract: The wireless sensor networks (WSNs) based on the IEEE 802.15.4 beacon enabled mode provide a deterministic resource allocation offered by the guaranteed time slot (GTS) mechanism which is ideal for real-time traffic applications that requires high quality of service (QoS). In the beacon enabled mode the active and optional inactive period is governed by superframe order (SO) and beacon order (BO). Adapting the duty cycle using the SO and BO is desirable to accommodate the changing context of the WSNs traffic for network optimisation. However, existing approaches assumed a fixed SO and BO and segregate the evaluation of the contention access period and the contention free period that forms the active segment. To improve the performance of the IEEE 802.15.4 protocol in respect of the trade-off between power consumption and end-to-end delay, within a required QoS, a combination of dynamic priorities for traffic differentiation and dynamic duty cycle adaptation in the GTS allocation process are introduced. This work demonstrates that the proposed solution provides significantly better performance than the standard allocation method by simultaneously satisfying QoS and service differentiation demands with considerable power savings which is essential for WSNs. The specific novel use of this solution is in an application scenario where the deployed network is situated in an assisted living environment with a rich suite of heterogeneous wireless based communications in place.

An adaptive competition-based clustering approach for wireless sensor networks

Abstract: Hierarchical architecture is an effective scheme to make wireless sensor networks (WSNs) scalable and energy-efficient Clustering the sensor nodes is a well-known two-layered architecture suitable for WSNs and has been extensively explored for different purposes and applications In this paper a novel clustering approach called the adaptive competition-based clustering approach (ACCA) is proposed for WSNs Selecting the cluster heads in the proposed ACCA is performed based upon a hybrid of local competition and the distances among the cluster heads First, by the new proposed competition scheme, the nodes which are with the high residual energy and closer to the centre of the density of the nodes are elected and form an initial set of cluster head candidates Then the candidates with suitable distances to other neighbor candidates are elected as the cluster heads The proposed algorithm is fast with a low time and message complexity It offers a longer lifetime for the networks, and at the same time, a proper level of fault tolerance The proposed ACCA is simple enough to be implemented in real systems Different simulation experiments are performed on different states and the algorithm is compared with some well-known and related clustering approaches The experiments suggest that in terms of longevity and fault-tolerance, ACCA outperforms the well-known and relevant clustering protocols LEACH, HEED, and EECABN

Adaptive multi-polling scheduler for QoS support of video transmission in IEEE 802.11e WLANs

Abstract: The 802.11E Task Group has been established to enhance quality of service (QoS) provision for time-bounded services in the current IEEE 802.11 medium access control protocol. The QoS is introduced throughout hybrid coordination function controlled channel access (HCCA) for the rigorous QoS provision. In HCCA, the station is allocated a fixed transmission opportunity (TXOP) based on its TSPEC parameters so that it is efficient for constant bit rate streams. However, as the profile of variable bit rate traffics is inconstant, they are liable to experience a higher delay especially in bursty traffic case. In this paper, we present a dynamic TXOP assignment algorithm called adaptive multi-polling TXOP scheduling algorithm (AMTXOP) for supporting the video traffics transmission over IEEE 802.11e wireless networks. This scheme invests a piggybacked information about the size of the subsequent video frames of the uplink streams to assist the hybrid coordinator accurately assign the TXOP according to actual change in the traffic profile. The proposed scheduler is powered by integrating multi-polling scheme to further reduce the delay and polling overhead. Extensive simulation experiments have been carried out to show the efficiency of the AMTXOP over the existing schemes in terms of the packet delay and the channel utilization.

Profitable areas in large-scale FTTH network optimization

Abstract: We present an optimization platform for Fiber-to-the-Home network design. The platform is capable of minimizing the capital expenditures (CAPEX) of network deployment by optimizing locations of optical equipment, signal splitters and cable cabinets, optimizing cable routes and types of cables as well as the number and types of optical cards and splitters. We present the architecture of the platform, the design process it implements, and the algorithms it deploys. The platform is used to indicate the parts of the design process that require complex optimization with dedicated algorithms and those that can be left to appropriately crafted engineering rules. We indicate that while keeping the computation time acceptable, much of the CAPEX savings can be obtained when locations of optical equipment are thoroughly optimized, cable routes are determined with plain engineering rules, and finally, signal splitting patterns are optimized carefully to lower the fiber count and thus the cost of cables.