Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

Recent Advances in MAC Protocols for the Energy Harvesting Based WSN: A Comprehensive Review

Abstract: Wireless sensor networks are catching the attention of the researchers in various fields like structural, healthcare monitoring, but the real world adoption is getting difficult due to its dependence on the battery power, so energy harvesting comes to its rescue. To utilize the harvested energy in the best manner, MAC protocols which control the transreceiver in a node are presented here. They are different from the battery powered WSN where the focus is on increasing the lifetime of the nodes, rather these protocols focus on improving the quality of the network. With optimal tradeoff between the infinite network lifetime and energy availability, MAC protocols need to be redesigned for energy harvesting based wireless sensor networks (EHWSN). In this paper first EH technology in wireless sensor networks is discussed. Then a survey of EH based MAC protocols is done in a classified manner. The comparison of the protocols is done based on the different metrics such as energy conservation factor, scalability, latency etc. State of the art literature survey is presented so that users have consolidated data to pick up the one based on their application requirement. Challenges specific to applications is presented along with the various gaps to give an insight into the future research directions. To the best of the author’s knowledge, review of all the EHWSN MAC protocols is not reported till date.

Hybridization of water wave optimization and sequential quadratic programming for cognitive radio system

Abstract: Nature-inspired algorithms are attracting attention of researchers due to their simplicity and flexibility. These algorithms are analyzed in terms of their key features like their diversity and adaptation, exploration and exploitation, as well as attraction and diffusion mechanisms. Every optimization algorithm needs to address the exploration and exploitation of a search space. In order to be successful, these algorithms need to establish a good ratio between exploration and exploitation. In this paper, water wave optimization (WWO) algorithm is integrated with sequential quadratic programming (SQP) called WWO–SQP for solving constrained high-dimensional problems. This new hybrid algorithm is able to explore globally through WWO and exploit locally through SQP to speed up the search process to find the best solution. The proposed hybrid algorithm is applied on cognitive radio (CR) system to optimize the allocation of frequency spectrum. This is done by sensing the various radio frequency parameters from the environment to the users on their demand. The reliability and efficiency of WWO–SQP algorithm are checked by using benchmark functions. In the optimization of CR system, the results obtained by the proposed algorithm are compared with various optimization algorithms. The results show that WWO–SQP has high accuracy, stability and outperforms other competitive algorithms.

An energy-efficient stable clustering approach using fuzzy-enhanced flower pollination algorithm for WSNs

Abstract: Due to advancement in the technology and need for machine-to-machine connectivity, wireless sensor network (WSN) overplays the role compared to other wireless networks. In this context, different applications based on WSNs need to be executed efficiently in terms of energy and communication. To achieve this, there is a need to collaborate among various devices at various levels. This can be achieved by the grouping of these devices, that is, through the clustering. Clustering-based routing is the most suitable approach to support for load balancing, fault tolerance and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering-based hierarchical approach, efficient CH selection algorithm and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, fuzzy-enhanced flower pollination algorithm-based threshold-sensitive energy-efficient clustering protocol is proposed to prolong the stability period of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.