Coordinated movement of multiple mobile sinks in a wireless sensor network for improved lifetime

Sink mobility is one of the most effective solutions for improving lifetime and has been widely investigated for the last decade. Algorithms for single-sink mobility are not directly applied to the multiple-sink case due to the latter’s specific challenges. Most of the approaches proposed in the literature use mathematical programming techniques to solve the multiple-sink mobility problem. However, doing so leads to higher complexities when traffic flow information for any possible sink-site combinations is included in the model. In this paper, we propose two algorithms that do not consider all possible sink-site combinations to determine migration points. We first present a centralized movement algorithm that uses an energy-cost matrix for a user-defined threshold number of combinations to coordinate multiple-sink movement. We also give a distributed algorithm that does not use any prior network information and has a low message exchange overhead. Our simulations show that the centralized algorithm gives better network lifetime performance compared to previously proposed MinDiff-RE, random movement, and static-sink algorithms. Our distributed algorithm has a lower network lifetime than centralized algorithms; sinks travel significantly less than in all the other schemes. © 2015, Koç and Korpeoglu

Sleep scheduling with expected common coverage in wireless sensor networks

Abstract Sleep scheduling, which is putting some sensor nodes into sleep mode without harming network functionality, is a common method to reduce energy consumption in dense wireless sensor networks. This paper proposes a distributed and energy efficient sleep scheduling and routing scheme that can be used to extend the lifetime of a sensor network while maintaining a user defined coverage and connectivity. The scheme can activate and deactivate the three basic units of a sensor node (sensing, processing, and communication units) independently. The paper also provides a probabilistic method to estimate how much the sensing area of a node is covered by other active nodes in its neighborhood. The method is utilized by the proposed scheduling and routing scheme to reduce the control message overhead while deciding the next modes (fullactive, semi-active, inactive/sleeping) of sensor nodes. We evaluated our estimation method and scheduling scheme via simulation experiments and compared our scheme also with another scheme. The results validate our probabilistic method for coverage estimation and show that our sleep scheduling and routing scheme can significantly increase the network lifetime while keep- ing the message complexity low and preserving both connectivity and coverage

Controlled Sink Mobility Algorithms for Wireless Sensor Networks

A wireless sensor network (WSN) consists of hundreds or thousands of sensor nodes organized in an ad hoc manner to achieve a predefined goal. Although WSNs have limitations in terms of memory and processors, the main constraint that makes WSNs different from traditional networks is the battery problem which limits the lifetime of a network. Different approaches are proposed in the literature for improving the network lifetime, including data aggregation, energy efficient routing schemes, and MAC protocols. Sink node mobility is also an effective approach for improving the network lifetime. In this paper, we investigate controlled sink node mobility and present a set of algorithms for deciding where and when to move a sink node to improve network lifetime. Moreover, we give a load-balanced topology construction algorithm as another component of our solution. We did extensive simulation experiments to evaluate the performance of the components of our mobility scheme and to compare our solution with static case and random movement strategy. The results show that our algorithms are effective in improving network lifetime and provide significantly better lifetime compared to static sink case and random movement strategy

An Energy-Efficient Scatternet Formation Algorithm for Bluetooth-Based Sensor Networks

In this paper, we propose an energy-efficient scatternet formation algorithm for Bluetooth based sensor networks. The algorithm is based on first computing a shortest path tree from the base station to all sensor nodes and then solving the degree constraint problem so that the degree of each node in the network is not greater than seven, which is a Bluetooth constaint. In this way, less amount of energy is spent in each round of communication in the sensor network. The algorithm also tries to balance the load evenly on the highenergy consuming nodes which are the nodes that are close to the base station. In this way, the lifetime of the first dying node is also prolonged. We obtained promising results in the simulations

DSSP: A Dynamic Sleep Scheduling Protocol for Prolonging the Lifetime of Wireless Sensor Networks ∗

This paper presents DSSP (Dynamic Sleep Scheduling Protocol), a centralized scheme for extending the lifetime of densely deployed wireless sensor networks by keeping only a necessary set of sensor nodes active. We present an algorithm for finding out which nodes should be put into sleep mode, and the algorithm preserves coverage and connectivity while trying to put as much nodes as possible into sleep mode. The algorithm is executed at the base station periodically. In this way, the network is reconfigured periodically, which also helps to a more even distribution of energy consumption load to sensor nodes. We evaluated our protocol via simulations and observed a significant increase in the lifetime, depending on the node density, while providing good coverage. 1

Distributed and Location-Based Multicast Routing Algorithms for Wireless Sensor Networks

Multicast routing protocols in wireless sensor networks are required for sending the same message to multiple different destinations. In this paper, we propose two different distributed algorithms for multicast routing in wireless sensor networks which make use of location information of sensor nodes. Our first algorithm groups the destination nodes according to their angular positions and forwards the multicast message toward each group in order to reduce the number of total branches in multicast tree which also reduces the number of messages transmitted. Our second algorithm calculates an Euclidean minimum spanning tree at the source node by using the positions of the destination nodes. The multicast message is forwarded to destination nodes according to the calculated MST. This helps in reducing the total energy consumed for delivering the message to all destinations by decreasing the number of total transmissions. Evaluation results show that the algorithms we propose are scalable and energy efficient, so they are good candidates to be used for multicasting in wireless sensor networks

Utilization-Based Dynamic Scheduling Algorithm for Wireless Mesh Networks

Channel access scheduling is one of the key components in the design of multihop wireless mesh networks (WMNs). This paper addresses the allocation/demand mismatch problem observed in oblivious WMN channel access scheduling schemes and proposes Utilization-Based Scheduling (UBS). UBS is a Spatial-TDMA- (STDMA-) based dynamic channel access scheduling scheme designed with the aim of increasing the application-level throughput. In UBS, each node has a weight, which is dynamically adjusted in accordance with the node's slot usage history and packet-queue occupancy. UBS is a fully distributed algorithm, where each node adjusts its own weight and makes pseudorandom transmission attempts using only the locally available information. To demonstrate the performance improvements of the dynamic weight adjustment, the performance of UBS is compared against other channel access scheduling schemes through extensive ns-2 simulations under both uniform and nonuniform traffic patterns.</p