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Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work. [ABSTRACT FROM AUTHOR]

This paper presents an opportunistic reception (OR) algorithm for energy-efficient transmission in cooperative wireless sensor networks (WSNs), where the characteristics of random linear network coding and the energy consumption property of WSNs are jointly considered. In OR, the sensor nodes in intermediate cluster generate the independent coding vector through simple forwarding or decoding-recoding manners opportunistically, so that the number of received packets can be reduced. To evaluate the algorithm, we derive the average number of received packets, the transmitting nodes, and decoding failure probability under specific assumption. The obtained theoretical and simulation results verify the effectiveness offered by the proposed approach. [ABSTRACT FROM AUTHOR]

Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. It can ensure the coverage degree of a region and prolong the network lifetime. In this paper, we focus on the k-coverage scheduling problem to guarantee k-coverage sensing and network connectivity. We consider both deterministic and stochastic sensing models of the sensors and adapt the results of deterministic sensing model to solve the sensor scheduling problem under the stochastic sensing model. We use regular pentagons to divide the sensing disks to solve the k-coverage problem. Each sensor node runs a stochastic k-coverage-preserving scheduling algorithm to determine its work modes, and redundant nodes can enter into sleep mode, while active nodes ensure the coverage of the network. Theoretical analysis and simulation results show that our algorithm can reduce the number of active nodes and extend the network lifetime significantly while maintaining a given coverage degree. [ABSTRACT FROM AUTHOR]

A large-scale deployment of femtocell BSs (FBSs) causes substantial energy consumption. This paper proposes a hybrid BS-cooperative power management (HBCPM) scheme with self-organized sleep mode in virtual cell-based femto networks. Firstly, HBCPM builds a leader-member virtual cell framework, in which only one FBS is a FBS leader (FL) and others are FBS members (FMs). Then, the FL acts as an autonomous entity and is responsible for detecting active calls in the virtual cell coverage, while the FMs without active connections can entirely shut down pilot transmissions and the related processing all the time. So it is suited for self-organizing networks (SONs). Based on the proposed scheme, the state transition model is established by the semi-Markov stochastic process, and the analytic formulas of average cumulative delay and interference time as well as the energy consumption are derived. Meanwhile, three prominent-related schemes are also studied by the proposed model. With the practical long-term evolution (LTE) system parameters and three-dimensional femtocell network model, the numerical simulation and theoretical analysis match pretty well, and the tradeoff between the energy consumption and average cumulative delay is also manifested. Moreover, simulation results show that the proposed algorithm outperforms other three schemes in terms of average cumulative interference time and the energy consumption. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of the connectivity control and the self-organized deployment/dispersion of a team of mobile ad hoc sensor nodes. First, to reduce redundant communication links while preserving global connectivity, a distributed link removal algorithm is developed that only requires local information of no more than two-hop neighbors. Secondly, for the purpose of preserving essential links while avoiding collisions, a combined piecewise-continuous motion controller is designed to regulate the motion of mobile sensors between two consecutive switches. The proposed hybrid control system can autonomously disperse a team of mobile sensors towards their final configuration with guaranteed connectivity and collision avoidance. Theoretical analysis and computer simulations have confirmed the efficiency and scalability of the proposed schemes. [ABSTRACT FROM AUTHOR]

This paper presents a novel multicast routing protocol for wireless sensor networks, named Multicast tree protocol with Pruning and Energy Balancing (MPEB) to disseminate data through a layered multicast tree with high-efficiency and low-power consumption. With pruning algorithm and energy balancing algorithm, MPEB can save energy and balance load. Pruning algorithm records and maintains backup parents for each child node, and thus it can detach possible nodes from the multicast tree and turn as many nodes as possible to sleep. Energy balancing algorithm protects nodes with low power from running out of energy and dying out, and thus it can balance total energy consumption of the whole network and prolong the network lifetime. The formal validations and simulations evaluate the performance of MPEB, which shows that MPEB has a distinct advantage over others in both reducing and balancing energy consumption. [ABSTRACT FROM AUTHOR]

Area coverage is one of the key issues for wireless sensor networks. It aims at selecting a minimum number of sensor nodes to cover the whole sensing region and maximizing the lifetime of the network. In this paper, we discuss the energy-efficient area coverage problem considering boundary effects in a new perspective, that is, transforming the area coverage problem to the target coverage problem and then achieving full area coverage by covering all the targets in the converted target coverage problem. Thus, the coverage of every point in the sensing region is transformed to the coverage of a fraction of targets. Two schemes for the converted target coverage are proposed, which can generate cover sets covering all the targets. The network constructed by sensor nodes in the cover set is proved to be connected. Compared with the previous algorithms, simulation results show that the proposed algorithm can prolong the lifetime of the network. [ABSTRACT FROM AUTHOR]