A game theoretic approach to balancing energy consumption in heterogeneous wireless sensor networks

Energy balancing is an effective technique in enhancing the lifetime of a wireless sensor network (WSN). Specifically, balancing the energy consumption among sensors can prevent losing some critical sensors prematurely due to energy exhaustion so that the WSN's coverage can be maintained. However, the heterogeneous hostile operating conditions—different transmission distances, varying fading environments, and distinct residual energy levels—have made energy balancing a highly challenging task. A key issue in energy balancing is to maintain a certain level of energy fairness in the whole WSN. To achieve energy fairness, the transmission load should be allocated among sensors such that, regardless of a sensor's working conditions, no sensor node should be unfairly overburdened. In this paper, we model the transmission load assignment in WSN as a game. With our novel utility function that can capture realistic sensors’ behaviors, we have derived the Nash equilibrium (NE) of the energy balancing game. Most importantly, under the NE, while each sensor can maximize its own payoff, the global objective of energy balancing can also be achieved. Moreover, by incorporating a penalty mechanism, the delivery rate and delay constraints imposed by the WSN application can be satisfied. Through extensive simulations, our game theoretic approach is shown to be effective in that adequate energy balancing is achieved and, consequently, network lifetime is significantly enhanced. Copyright © 2012 John Wiley & Sons, Ltd.     

A hierarchical approach to position-based multicast for mobile ad-hoc networks

In this paper we present Scalable Position-Based Multicast (SPBM), a multicast routing protocol for ad-hoc networks. SPBM uses the geographic position of nodes to provide a highly scalable group membership scheme and to forward data packets in a way that is very robust to changes in the topology of the network. SPBM bases the forwarding decision on whether or not there are group members located in a given direction, allowing a hierarchical aggregation of membership information. The farther away a region is from an intermediate node, the higher the level of aggregation for this region should be. Because of aggregation, the overhead for group membership management scales logarithmically with the number of nodes and is independent of the number of multicast senders for a given multicast group. Furthermore, we show that group management overhead is bounded by a constant if the frequency of membership updates is scaled down with the aggregation level. This scaling of the update frequency is reasonable since the higher the level of aggregation is, the lower the number of membership changes for the aggregate will be. The performance of SPBM is investigated by means of simulation, including a comparison with ODMRP, and through mathematical analysis. We also describe an open source kernel implementation of SPBM that has been successfully deployed on hand-held computers.     

Interference power statistics in ad-hoc and sensor networks

There exist accurate calculation methods for estimation of interference power sum statistics in fixed-topology wireless networks based on the log-normal shadowing radio model. Here we publish essential additions to these estimation methods to expand their use to sensor networks and ad-hoc networks with changing topology. In our calculations we take into account radio propagation conditions, density of nodes, size of the network, traffic load per node and MAC protocol characteristics. The accuracy of our calculation method is verified by simulations. We highlight the influence of MAC protocols on interference and show that an increase in network size or in node density does not necessarily lead into higher interference values. Our results can be deployed to estimate the network capacity. Ramin Hekmat received M.Sc. degree in electrical engineering from Delft University of Technology (TU Delft) in the Netherlands in 1990. He worked since then for several telecommunication companies in the Netherlands and the United States in Research and Development as well as managerial positions. In September 2005 he obtained Ph.D. degree for his work related to Ad-hoc Networks form TU Delft. Currently he is working as assistant professor in the faculty of Electrical Engineering, Mathematics and Computer Science of TU Delft. His prime research interest includes multi-user communication systems, wireless communications and peer-to-peer networks. Email: r.hekmat@ewi.tudelft.nl Mailing address: Delft University of Technology Electrical Engineering, Mathematics and Computer Science P.O. Box 5031 2600 GA Delft The Netherlands. Piet Van Mieghem has obtained the Master and Ph. D. in Electrical Engineering from the K.U.Leuven (Belgium) in 1987 and 1991, respectively. He has joined the Interuniversity Micro Electronic Center (IMEC) from 1987-1991. He was a visiting scientist at MIT, department of electrical engineering from 1992-1993. From 1993 to 1998, he was working in Alcatel Corporate Research Center in Antwerp where he has gained experience in performance analysis of ATM systems and network architectural concepts of both ATM networks (PNNI) and the Internet. Currently, he is full professor at Delft University of Technology with a chair in telecommunication networks. The main theme of the research is evolution of the Internet architecture towards a broadband and QoS-aware network. Email: p.vanmieghem@ewi.tudelft.nl Mailing address: Delft University of Technology Electrical Engineering, Mathematics and Computer Science P.O. Box 5031 2600 GA Delft The Netherlands.     

A hybrid,game theory based,and distributed clustering protocol for wireless sensor networks

Clustering has been well known as an effective way to reduce energy dissipation and prolong network lifetime in wireless sensor networks. Recently, game theory has been used to model clustering problem. Each node is modeled as a player which can selfishly choose its own strategies to be a cluster head (CH) or not. And by playing a localized clustering game, it gets an equilibrium probability to be a CH that makes its payoff keep equilibrium. In this paper, based on game theory, we present a clustering protocol named Hybrid, Game Theory based and Distributed clustering. In our protocol, we specifically define the payoff for each node when choosing different strategies, where both node degree and distance to base station are considered. Under this definition, each node gets its equilibrium probability by playing the game. And it decides whether to be a CH based on this equilibrium probability that can achieve a good trade-off between minimizing energy dissipation and providing the required services effectively. Moreover, an iterative algorithm is proposed to select the final CHs from the potential CHs according to a hybrid of residual energy and the number of neighboring potential CHs. Our iterative algorithm can balance the energy consumption among nodes and avoid the case that more than one CH occurs in a close proximity. And we prove it terminates in finite iterations. Simulation results show that our protocol outperforms LEACH, CROSS and LGCA in terms of network lifetime.     

A game theoretical approach to model the channel selection dynamics in non-coordinated IEEE 802.11 networks

The massive deployment of Wireless Local Area Networks has made interference mitigation between neighboring networks a challenging issue. These uncoordinated access networks aim at improving their operation by choosing the best wireless channel available, characterizing a competition over the restricted set of possible channels. This work analyses this competition using Game Theory and Markov Chains models, showing that such competitive behavior can lead to Nash Equilibria and that outcomes mostly will not be maximal. Additionally, partially and fully cooperative models are proposed and evaluated, allowing (a) individual players to increase global results using arbitrarily computed and non-rational moves, and (b) achieving maximal outcomes when considering the cooperation of up to all players.

     

Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks

Due to inherent issue of energy limitation in sensor nodes, the energy conservation is the primary concern for large‐scale wireless sensor networks. Cluster‐based routing has been found to be an effective mechanism to reduce the energy consumption of sensor nodes. In clustered wireless sensor networks, the network is divided into a set of clusters; each cluster has a coordinator, called cluster head (CH). Each node of a cluster transmits its collected information to its CH that in turn aggregates the received information and sends it to the base station directly or via other CHs. In multihop communication, the CHs closer to the base station are burdened with high relay load; as a result, their energy depletes much faster as compared with other CHs. This problem is termed as the hot spot problem. In this paper, a distributed fuzzy logic‐based unequal clustering approach and routing algorithm (DFCR) is proposed to solve this problem. Based on the cluster design, a multihop routing algorithm is also proposed, which is both energy efficient and energy balancing. The simulation results reinforce the efficiency of the proposed DFCR algorithm over the state‐of‐the‐art algorithms, ie, energy‐aware fuzzy approach to unequal clustering, energy‐aware distributed clustering, and energy‐aware routing algorithm, in terms of different performance parameters like energy efficiency and network lifetime.     

An overlay approach to data security in ad-hoc networks

While it has been argued that application-layer overlay protocols can enhance services in mobile ad-hoc networks, hardly any empirical data is available on the throughput and delay performance achievable in this fashion. This paper presents performance measurements of an application-layer overlay approach that ensures integrity and confidentiality of application data in an ad-hoc environment. A key management and encryption scheme, called neighborhood key method, is presented where each node shares secrets only with authenticated neighbors in the ad-hoc network, thus avoiding global re-keying operations. All proposed solutions have been implemented and empirically evaluated in an existing software system for application-layer overlay networking. Results from indoor and outdoor measurement experiments with mobile handheld devices provide insight into the performance and overhead of overlay networking and application-layer security services in ad-hoc networks.     

Distributed phase-shift beamforming power balancing in ad-hoc and sensor networks

Ad-hoc and sensor networks are a well-studied area which gained a lot of attention in the research in the last decades. Two of the problems of battery-powered radio devices are limited transmitter power and finite amount of energy. This paper continues the path opened by the development of a new technology for radio communication which allows cluster communication beyond the horizon of each individual transmitter and the distribution of power need among the modules forming a cluster. This in terms decreases the average power need per device and contributes to a longer lifetime of the entire network.     

Experimental evaluation of game theoretic power allocation in MIMO ad-hoc networks

Multiple input multiple output (MIMO) communication systems in an ad-hoc network can provide high spectral efficiency. Several resource allocation methods have been presented and experimentally demonstrated to improve performance in a resource limited environment. Recently, a game theoretic method has been published with promising results. The goal of this paper is to present simulation and experimental results for this game theoretic technique.     

Signaling game approach to improve the MAC protocol in the underwater wireless sensor networks

Underwater sensor networks (UWSNs) are instructed for critical applications like military surveillance and underwater oil spills that conducted in a very massive three‐dimensional (3‐D) space that needs many underwater nodes (UNs) to cover the target area. Those UNs are not easy to recharge and cannot exploit solar power. MAC protocols deployed for UWSN ought to consider the energy efficiency, so as, to extend the network lifetime with total connectivity and significant throughput. Terrestrial MAC protocols could not be used for UWSN due to long and unpredictable propagation delay. Consequently, the development of a new MAC protocol for the harsh environment as underwater is a challenging task. In this study, we focus on the deployment of TDMA in UWSN for this, two schemes entitled TDMA slot sharing (TSS) and free time slots reallocation (FTSR) are proposed. Received data stored in the buffer waiting for processing and forwarding might lead to an unlimited data transfer latency those results in the buffer overflow. Otherwise, free time slots appearing during the communication process resulting from dead nodes increase uselessly sleep time for the rest of the nodes. Both schemes based on signaling game are proposed to overcome those problems, TSS is used to enable the slot sharing between UNs during the communication process to reduce the buffer overflow. FTSR scheme aims to increase the throughput of UNs by allowing the reuse of free time slots. Numerical results conducted in this work show good improvement in the network performance concerning throughput.     

A game theoretic approach to video streaming over peer-to-peer networks

We consider the problem of foresighted multimedia resource reciprocation in peer-to-peer (P2P) networks, which consist of rational peers aiming at maximizing their individual utilities. We introduce an artificial currency (credit) to take into account the characteristics of different parts of the video signal. The resource reciprocation with the proposed credit metric can be formulated as a stochastic game, in which the peers determine their optimal strategies using Markov Decision Process (MDP) framework. The introduced framework can be applied to the general video coding, and in particular, is suitable for the scalable video where various parts of the encoded bit stream have significantly different importance for the video quality.     

Fast randomized algorithm for 2-hops clustering in vehicular ad-hoc networks

Vehicular Ad-Hoc Networks (VANETs) enable inter vehicle wireless communication as well as communication with road side equipment. Warning messages can be exchanged among nearby vehicles, helping to predict dangerous situations, and thus improving road safety. Such safety messages require fast delivery and minimal delay to local areas, in order for them to be effective. Therefore, a fast and efficient channel access scheme is required. A feasible solution, derived from the Mobile Ad-Hoc Networks (MANETs) field, groups nodes into smaller manageable sections called clusters. Such an approach can be beneficial for locally delivering messages under strict time constraints. In this paper, a Hierarchical Clustering Algorithm (HCA) is presented. HCA is a distributed randomized algorithm, which manages channel access by forming three hierarchy clusters. The proposed channel access scheme enables delay bounded reliable communication. Unlike other common clustering algorithm for VANETs, HCA does not require the knowledge of the vehicles’ locations. This feature guarantees accurate operation even when localization systems such as GPS are not available. The running time and message complexity were analyzed and simulated. Simulation results show that the algorithm behaves well especially under realistic mobility patterns; therefore, it is a suitable solution for channel access scheme for VANETs.     

LIDAR: a protocol for stable and energy-efficient clustering of ad-hoc multihop networks

Clustering has been proposed as a promising method for simplifying the routing process in mobile ad hoc networks (MANETs). The main objective in clustering is to identify suitable node representatives, i.e. cluster heads (CHs) to store routing and topology information; CHs should be elected so as to maximize clusters stability, that is to prevent frequent cluster re-structuring. Since CHs are engaged on packet forwarding they are prone to rapidly drop their energy supplies, hence, another important objective of clustering is to prevent such node failures. Recently proposed clustering algorithms either suggest CH election based on node IDs (nodes with locally lowest ID value become CHs) or take into account additional metrics (such as energy and mobility) and optimize initial clustering. Yet, the former method is biased against nodes with low IDs (which are likely to serve as CHs for long periods and therefore run the risk of rapid battery exhaustion). Similarly, in the latter method, in many situations (e.g. in relatively static topologies) re-clustering procedure is hardly ever invoked; hence initially elected CHs soon suffer from energy drainage. Herein, we propose LIDAR, a novel clustering method which represents a major improvement over alternative clustering algorithms: node IDs are periodically re-assigned so that nodes with low mobility rate and high energy capacity are assigned low ID values and, therefore, are likely to serve as CHs. Therefore, LIDAR achieves stable cluster formations and balanced distribution of energy consumption over mobile nodes. Our protocol also greatly reduces control traffic volume of existing algorithms during clustering maintenance phase, while not risking the energy availability of CHs. Simulation results demonstrate the efficiency, scalability and stability of our protocol against alternative approaches.     

A novel approach based on bio-inspired efficient clustering algorithm for large-scale heterogeneous wireless sensor networks

In large-scale heterogeneous wireless sensor networks (WSNs), clustering is particularly significant for lowering sensor nodes (SNs) energy consumption and creating algorithm more energy efficient. The selection of cluster heads (CHs) is a crucial task in the clustering method. In this paper, optimised K-means clustering algorithm and optimised K-means based modified intelligent CH selection based on BFOA for large-scale network (lar-OK-MICHB) is hybridised for CH selection process. Here, we utilised the extended capabilities of OK-MICHB algorithm for large-scale network. Furthermore, in many applications where energy is a primary constraint, such as military surveillance and natural disaster prediction, the stability region is also a significant factor, with a longer network lifespan being a primary requirement. In the proposed approach, only the CH selection is made after every round in place of cluster and CH change as done in conventional hierarchical algorithm. The simulation results reveal that, while keeping the distributive structure of WSNs, suggested lar-OKMIDEEC can locate real greater leftover energy nodes for selection of CH without utilising randomise or estimated procedures. Furthermore, as compared with the multi-level MIDEEC protocol, this offers a larger stability region with 68.96% increment, more consistent selection of CH in every round, and greater packets (i.e., in numbers) received at the base station (BS) with a longer network lifetime with 327% increment.     

A game theoretical distributed approach for opportunistic caching strategy

Wireless Networks - Wireless network virtualization (WNV) has been a hot topic recently, which can provide the customized service to construct virtual networks for various requirements quickly and...     

面向数据聚集有向分簇算法在传感器网络中的应用

传统的分簇算法有在数据回传现象和节点能量利用率低的缺点,为了解决这个问题,文章提出了面向数据聚集的有向分簇算法。其核心思想是使网络中所有的节点传输方向全部都沿着接近Sink的方向进行,这样就解决了传统的分簇算法存在的问题。测试结果表明,此算法大大提高了能量的利用率,同时传感器网络的生存周期也得到了延长。     

A control theoretical approach to congestion control in packet networks

In this paper, we introduce a control theoretical analysis of the closed-loop congestion control problem in packet networks. The control theoretical approach is used in a proportional rate controller, where packets are admitted into the network in accordance with network buffer occupancy. A Smith Predictor is used to deal with large propagation delays, common to high speed backbone networks. The analytical approach leads to accurate predictions regarding both transients as well as steady-state behavior of buffers and input rates. Moreover, it exposes tradeoffs regarding buffer dimensioning, packet loss, and throughput.     

SCE-PSO based clustering approach for load balancing of gateways in wireless sensor networks

Wireless Networks - Wireless sensor networks (WSNs) consist of spatially distributed low power sensor nodes and gateways along with sink to monitor physical or environmental conditions. In...     

Dynamic clustering approach based on wireless sensor networks genetic algorithm for IoT applications

Energy is vital parameter for communication in Internet of Things (IoT) applications via Wireless Sensor Networks (WSN). Genetic algorithms with dynamic clustering approach are supposed to be very effective technique in conserving energy during the process of network planning and designing for IoT. Dynamic clustering recognizes the cluster head (CH) with higher energy for the data transmission in the network. In this paper, various applications, like smart transportation, smart grid, and smart cities, are discussed to establish that implementation of dynamic clustering computing-based IoT can support real-world applications in an efficient way. In the proposed approach, the dynamic clustering-based methodology and frame relay nodes (RN) are improved to elect the most preferred sensor node (SN) amidst the nodes in cluster. For this purpose, a Genetic Analysis approach is used. The simulations demonstrate that the proposed technique overcomes the dynamic clustering relay node (DCRN) clustering algorithm in terms of slot utilization, throughput and standard deviation in data transmission.