Game theory (GT) is a mathematical method that describes the phenomenon of conflict and cooperation between intelligent rational decision-makers. In particular, the theory has been proven very useful in the design of wireless sensor networks (WSNs). This article surveys the recent developments and findings of GT, its applications in WSNs, and provides the community a general view of this vibrant research area. We first introduce the typical formulation of GT in the WSN application domain. The roles of GT are described that include routing protocol design, topology control, power control and energy saving, packet forwarding, data collection, spectrum allocation, bandwidth allocation, quality of service control, coverage optimization, WSN security, and other sensor management tasks. Then, three variations of game theory are described, namely, the cooperative, non-cooperative, and repeated schemes. Finally, existing problems and future trends are identified for researchers and engineers in the field.

https://www.mdpi.com/1424-8220/12/7/9055/pdf

Game theory for Wireless Sensor Networks: a survey.

Game theory for energy efficiency in Wireless Sensor Networks

IEEE 802.15.4 is the de facto standard for Wireless Sensor Networks (WSNs) that outlines the specifications of the PHY layer and MAC sub-layer in these networks. The MAC protocol is needed to orchestrate sensor nodes access to the wireless communication medium. Although distinguished by a set of strengths that contributed to its popularity in various WSNs, IEEE 802.15.4 MAC suffers from several limitations that play a role in deteriorating its performance. Also, from a practical perspective, 80.15.4-based networks are usually deployed in the vicinity of other wireless networks that operate in the same ISM band. This means that 802.15.4 MAC should be ready to cope with interference from other networks. These facts have motivated efforts to devise improved IEEE 802.15.4 MAC protocols for WSNs. In this paper we provide a survey for these protocols and highlight the methodologies they follow to enhance the performance of the IEEE 802.15.4 MAC protocol.

A Survey of Beacon-Enabled IEEE 802.15.4 MAC Protocols in Wireless Sensor Networks

Wireless Sensor Network (WSN) is a promising technology for many applications, such as industrial, environment, and health-care application. The first requirement of WSN is energy efficiency in order to increase the network node lifetime. The second is reliability because packet drop cannot be tolerated in critical time applications. In this paper, we use NS2 simulation to evaluate and analyze the IEEE 802.15.4 standard in multi-hop WSN with a tree topology base on IEEE 802.15.4. Beacon enabled mode is used slotted CSMA/CA and non-beacon enabled mode is used unslotted CSMA/CA. Performance of beacon enabled and non-beacon enabled were evaluated and analyzed to understand the impact of protocol parameters such as Superframe Order (SO), Beacon Order (BO), and Traffic Load. The performance of the network which have been evaluated in detail are the throughput, energy consumption, end to end delay, packet success probability, drop packets and the percentage of the energy efficiency. The simulation result show that of beacon enabled is better than non beacon enabled in terms of the throughput, drop packet, energy consumption, and energy efficiency.

Performance of multi-hop networks using beacon and non-beacon scheduling in Wireless Sensor Network (WSN)

Cloud computing is experiencing phenomenal growth and there are now many vendors offering their cloud services. In cloud computing, cloud providers cooperate together to offer their computing resource as a utility and software as a service to customers. The demands and the price of cloud service should be negotiated between providers and users based on the Service Level Agreement (SLA). In order to help cloud providers achieving an agreeable price for their services and maximizing the benefits of both cloud providers and clients, this paper proposes a cloud pricing system consisting of hierarchical system, M/M/c queuing model and pricing model. Simulation results verify the efficiency of our proposed system.

A Hierarchical Cloud Pricing System

As one of the most widely investigated topology control mechanisms of wireless sensor networks (WSNs), the clustering algorithm provides energy efficient communications by reducing transmission overhead and enhancing transmission reliability. Through the previous forms of noncooperative games, the behavior of each sensor node (SN) is individual in WSNs; accordingly, it engenders uneven distribution of residual energy across SNs and expedites network partition. To balance energy consumption of SNs and increase network lifetime and stability, a cooperative game theoretic model of clustering algorithms is provided for assigning feasible allocations of energy cost. Moreover, from the outcome of this model, we propose and analyze a cooperative clustering approach for global optimization with the capacity of sensing data transmission and energy efficiency. The key idea is that SNs should trade off individual cost with network-wide cost. In the algorithm, we develop conditions to form coalitions considering residual energy, transmission distance and number of SNs in a cluster adapting to various WSNs. Furthermore, we present performance evaluation and comparison of the existing clustering algorithms with our approach quantitatively with respect to network lifetime, data transmission capacity and energy efficiency. Comparing with other approaches through the simulation, our scheme can surely guarantee to prolong network life-time and improve data transmission capacity up to 5.8% and 35.9%, respectively.

A cooperative game theoretic approach to clustering algorithms for wireless sensor networks

As one of the most widely implemented standards for wireless networks, IEEE 802.15.4 defines physical and MAC specifications for low data rate wireless personal area networks (WPANs). To accurately analyze the performance of slotted CSMA/CA (SCSMA) algorithms for saturated uplink traffic with acknowledgement (ACK) and non-ACK modes, we adopt an embedded Markov chain based model in the MAC layer of the standard. From the analytic model, we optimize network throughput considering the number of 802.15.4 devices and the data payload by nonlinear programming (NLP). Moreover, according to analytical results of optimization, we propose an adaptive backoff mechanism for maximizing throughput by an approximate and simple Markov model. Furthermore, we present performance evaluation and comparison of IEEE 802.15.4 SCSMA protocol with our approach quantitatively with respect to saturation throughput and probability of successful transmission. Comparing with the SCSMA protocol of IEEE standard through the simulation, our scheme can improve network throughput with non-ACK and ACK modes up to 4.8% and 8.1% on average, respectively. The performance analysis also shows that the network scalability is improved, that is the system can accommodate more contending devices in our proposal.

An analytical approach to optimization of throughput for IEEE 802.15.4 slotted CSMA/CA networks

1.1 Wireless sensor networks Wireless sensor networks have been made viable by the convergence of micro-electromechanical systems technology, wireless communications and digital electronics (Akyildiz et al., 2002). They are expected to consist of a large number of inexpensive sensor nodes, each having sensing, data processing and communicating components with limited computational and communication power. To provide various measurements such as light, temperature, pressure and activity, these low-cost, low-power, multifunctional sensor nodes have been widely deployed in a vast variety of environments for commercial, civil, and military applications such as surveillance, vehicle tracking, climate, etc.. However, a single sensor’s view of the environment is restricted both in range and in accuracy, due to it only covers a limited physical area and may produce noisy data by the quality of the hardware. Accordingly, aggregation of the individual surveillance allows users to accurately and reliably monitor an environment. Once sensor nodes are deployed throughout an area, they collect data from the environment and automatically establish dedicated networks to transmit their data to a base station. The nodes collaborate to gather data and extend the operating lifetime of the entire system. Wireless sensor networks offer a longevity, robustness, and ease of deployment that is ideal for environments where maintenance or battery replacement may be inconvenient or impossible (Hac, 2003). In recent years, with the rapid development of embedded systems including energy efficient devices, hardware/software co-design and networking support, sensor nodes have been smaller in size and more efficient in data processing and transmission. However, they are still limited in power, memory and computational capacities. As a result, the key challenge is to maximize the lifetime of sensor nodes due to the fact that it is not feasible to replace the batteries of thousands of nodes.

/pdf/cooperative-clustering-algorithms-for-wireless-sensor-4qpaz6okbm.pdf

Cooperative Clustering Algorithms for Wireless Sensor Networks

As one of the most widely investigated studies in wireless sensor networks (WSNs), multihop networking is increasingly developed and applied for achieving energy efficient communications and enhancing transmission reliability. To accurately and realistically analyze the performance metric (energy efficiency), firstly we provide a measurement of the energy dissipation for each state and establish a practical energy consumption model for a WSN. According to the analytical model of connectivity, Gaussian approximation approaches to experimental connection probability are expressed for optimization problem on energy efficiency. Moreover, for integrating experimental results with theories, we propose the methodology in multihop wireless sensor networks to maximize efficiency by nonlinear programming, considering energy consumptions and the total quantity of sensing data to base station. Furthermore, we present evaluations adapting to various wireless sensor networks quantitatively with respect to energy efficiency and network configuration, in view of connectivity, the length of data, maximum number of hops and total number of nodes. As the consequence, the realistic analysis can be used in practical applications, especially on self-organization sensor networks. The analysis also shows correlations between the efficiency and maximum number of hops, that is the multihop systems with several hops can accommodate enough devices in ordinary applications. In this paper, our contribution distinguished from others is that our model and analysis are extended from experiments. Therefore, the results of analysis and proposal can be conveniently applied to actual networks. key words: energy efficiency, multihop wireless sensor networks, optimization, realistic analysis, connectivity, nonlinear programming

Hui Jing

Papers

A cooperative game theoretic approach to clustering algorithms for wireless sensor networks

An analytical approach to optimization of throughput for IEEE 802.15.4 slotted CSMA/CA networks

Cooperative Clustering Algorithms for Wireless Sensor Networks

Realistic Analysis of Energy Efficiency in Multihop Wireless Sensor Networks

A Graphical Game Theoretic Approach to Optimization of Energy Efficiency in Multihop Wireless Sensor Networks