A Review of Energy Conservation in Wireless Sensor Networks

In wireless sensor networks, energy efficiency plays a major role to determine the lifetime of the network. The network is usually powered by a battery which is hard to recharge. Hence, one major challenge in wireless sensor networks is the issue of how to extend the lifetime of sensors to improve the efficiency. In order to reduce the rate at which the network consumes energy, researchers have come up with energy conservation techniques, schemes and protocols to solve the problem. This paper presents a brief overview of wireless sensor networks, outlines some causes of its energy loss and some energy conservation schemes based on existing techniques used in solving the problem of power management. Keywords: Wireless sensor network, Energy conservation, Duty cycling and Energy efficiency

Improving Maximum Data Collection Based On Pre-Specified Path Using a Mobile Sink for WSN

Data aggregation is one of the challenging issues which are faced in the wireless sensor network by using Energy Harvesting Sensors. Data collection in a fixed pre-defined path with time varying characteristic forms a major problem in Energy Harvesting Sensor Networks. In the proposed work the Adjustment based allocation method is used to allocate fixed time slots to each sensor nodes in which the network throughput can be increased with less energy consumption. The mobile sink transmits the polling message to all the nodes within the transmission range and makes decision based on the profits gained by the sensor nodes in each timeslot. The NP-Hard problem is defined with the form of reducing the complexity of the sensor nodes where larger number of data can be collected from the environment. The data collection throughput is maximized with the use of optimized path for the mobile sink in the network. This record was migrated from the OpenDepot repository service in June, 2017 before shutting down

Lifetime Maximization of Wireless Sensor Networks with a Mobile Source Node

We study the problem of routing in sensor networks where the goal is to maximize the network's lifetime. Previous work has considered this problem for fixed-topology networks. Here, we add mobility to the source node, which requires a new definition of the network lifetime. In particular, we redefine lifetime to be the time until the source node depletes its energy. When the mobile node's trajectory is unknown in advance, we formulate three versions of an optimal control problem aiming at this lifetime maximization. We show that in all cases, the solution can be reduced to a sequence of Non- Linear Programming (NLP) problems solved on line as the source node trajectory evolves.Comment: A shorter version of this work will be published in Proceedings of 2016 IEEE Conference on Decision and Contro

Path-Constrained Data Gathering Scheme

Several studies in recent years have considered the use of mobile elements for data gathering in wireless sensor networks so as to reduce the need for multi-hop forwarding among the sensor nodes and thereby prolong the network lifetime Since typically practical constraints preclude a mobile element from visiting all nodes in the sensor network the solution must involve a combination of a mobile element visiting a subset of the nodes cache points while other nodes communicate their data to the cache points wirelessly This leads to the optimization problem of minimizing the communication distance of the sensor nodes while keeping the tour length of the mobile element below a given constraint In this paper we investigate the problem of designing the mobile elements tours such that the length of each tour is below a per-determined length and the number of hops between the tours and the nodes not included in the tour is minimized To address this problem we present an algorithmic solution that consider the distribution of the nodes during the process of building the tours We compare the resulting performance of our algorithm with the best known comparable schemes in the literatur

Ferry–Based Directional Forwarding Mechanism for Improved Network Life-Time in Cluster-Based Wireless Sensor Network

Considerable energy saving can be achieved with mobility-based wireless sensor networks (WSN's), where a mobile node (ferry) visits sensing nodes in a network to collect sensed data. However, the critical issues of such WSN's are limited networks lifetime and high data latency, these critical issues are due to the slow mobility and relatively long route distance for ferries to collect and forward data to the sink. Incorporating ferries in WSNs eliminates the need for multi-hop forwarding of data, and as a result, reduce energy consumption at sensing nodes. In this paper, we introduce the One Hop Cluster-Head Algorithm (OHCH), where a subset of ferries serve as cluster heads (CH), travel between nodes with short distance mobility, collect data originated from sources, and transfer it to the sink with minimum hop count possible, this approach can achieve more balance between network energy saving and data collection delay, also, it is an efficient design to combine between ferries and noise

Data Gathering with Tour Length-Constrained

In this paper, given a single mobile element and a time deadline, we investigate the problem of designing the mobile element tour to visit subset of nodes, such that the length of this tour is bounded by the time deadline and the communication cost between nodes outside and inside the tour is minimized. The nodes that the mobile element tour visits, works as cache points that store the data of the other nodes. Several algorithms in the literature have tackled this problem by separating two phases; the construction of the mobile element tour from the computation of the forwarding trees to the cache points. In this paper, we propose algorithmic solutions that alternate between these phases and iteratively improves the outcome of each phase based on the result of the other. We compare the resulting performance of our solutions with that of previous work

Minimum Bend Shortest Rectilinear Route Discovery for a Moving Sink in a Grid Based Wireless Sensor Network

In a rectilinear route, a moving sink is restricted to travel either horizontally or vertically along the connecting edges. We present a new algorithm that finds the shortest round trip rectilinear route covering the specified nodes in a grid based Wireless Sensor Network.  The proposed algorithm determines the shortest round trip travelling salesman path in a two-dimensional grid graph. A special additional feature of the new path discovery technique is that it selects that path which has the least number of corners (bends) when more than one equal length shortest round trip paths are available. This feature makes the path more suitable for moving objects like Robots, drones and other types of vehicles which carry the moving sink. In the prosed scheme, the grid points are the vertices of the graph and the lines joining the grid points are the edges of the graph. The optimal edge set that forms the target path is determined using the binary integer programming

Minimum Bend Shortest Rectilinear Route Discovery for a Moving Sink in a Grid Based Wireless Sensor Network

In a rectilinear route, a moving sink is restricted to travel either horizontally or vertically along the connecting edges. We present a new algorithm that finds the shortest round trip rectilinear route covering the specified nodes in a grid based Wireless Sensor Network.  The proposed algorithm determines the shortest round trip travelling salesman path in a two-dimensional grid graph. A special additional feature of the new path discovery technique is that it selects that path which has the least number of corners (bends) when more than one equal length shortest round trip paths are available. This feature makes the path more suitable for moving objects like Robots, drones and other types of vehicles which carry the moving sink. In the prosed scheme, the grid points are the vertices of the graph and the lines joining the grid points are the edges of the graph. The optimal edge set that forms the target path is determined using the binary integer programming