H. Jamali Rad, B. Abolhassani, M. Abdizadeh,
Volume 8, Issue 3 (9-2012)
Abstract
In this paper, we study the problem of power efficient tracking interval management for distributed target tracking wireless sensor networks (WSNs). We first analyze the performance of a distributed target tracking network with one moving object, using a quantitative mathematical analysis. We show that previously proposed algorithms are efficient only for constant average velocity objects however, they do not ensure an optimal performance for moving objects with acceleration. Towards an optimal performance, first, we derive a mathematical equation for the estimation of the minimal achievable power consumption by an optimal adaptive tracking interval management algorithm. This can be used as a benchmark for energy efficiency of these adaptive algorithms. Second, we describe our recently proposed energy efficient blind adaptive time interval management algorithm called Adaptive Hill Climbing (AHC) in more detail and explain how it tries to get closer to the derived optimal performance. Finally, we provide a comprehensive performance evaluation for the recent similar adaptive time interval management algorithms using computer simulations. The simulation results show that using the AHC algorithm, the network has a very good performance with the added advantage of getting 9 % closer to the calculated minimal achievable power consumption compared with that of the best previously proposed energy efficient adaptive time interval management algorithm.
A. Pathak,
Volume 16, Issue 4 (12-2020)
Abstract
It is very difficult and expensive to replace sensor node battery in wireless sensor network in many critical conditions such as bridge supervising, resource exploration in hostile locations, and wildlife safety, etc. The natural choice in such situations is to maximize network lifetime. One such approach is to divide the sensing area of wireless sensor network into clusters to achieve high energy efficiency and to prolong network lifetime. In this paper, an Artificial Bee Colony Inspired Clustering Solution (ABCICS) is introduced. The proposed protocol selects the head of the cluster with optimal fitness function. The fitness function comprises the residual energy of node, node degree, node centrality, and distance from base station to node. When cluster-head with high energy node transmits the data to the base station, it further minimizes the energy consumption of the sensor network. The presented protocol is compared with LEACH, HSA-PSO, and MHACO-UC. Simulation experiments show the effectiveness of our approach to enhance the network lifetime.
Ankit Saxena,
Volume 21, Issue 4 (11-2025)
Abstract
The performance of wireless networks depends on measuring the radio characteristics between the Access Point (AP) and Client Station (STA) within the same Base Service Set (BSS). In areas with high demand for wireless services, multiple wireless networks may overlap, causing interference and negatively impacting the performance of individual users and networks. This interference makes wireless radio channels more susceptible to interference from surrounding energy, directly affecting wireless networks' throughput. A new spatial reuse IEEE802.11ax standard has provided the solution to address this issue. This standard performs a clear channel assessment procedure between the AP and STA before assigning the channel for traffic, thus reducing channel collision and improving the effectiveness of radio resources in wireless networks. Additionally, the quality and availability of radio resources of overlaying networks would improve the usage of radio channels. This study assesses how spatial reuse, combined with different modulation with coding schemes and clear channel assessment, affects channel throughput. The results show that integrating spatial reuse can boost channel throughput by 18-20%, significantly enhancing network performance.
