Task Scheduling is a complex combinatorial optimization problem and known to be an NP hard. It is an important challenging issue in multiprocessor computing systems. Discrete Particle Swarm Optimization (DPSO) is a newly developed swarm intelligence technique for solving discrete optimization problems efficiently. In DPSO, each particle should limit its communication with the previous best solution and the best solutions of its neighbors. This learning restriction may reduce the diversity of the algorithm and also the possibility of occurring premature convergence problem. In order to address these issues, the proposed work presents a hybrid version of DPSO which is a combination of DPSO and Cyber Swarm Algorithm (CSA). The efficiency of the proposed algorithm is evaluated based on a set of benchmark instances and the performance criteria such as makespan, mean flow time and reliability cost.
Recent development in wireless sensor application such as surveillance, traffic monitoring and storage of potential relevant from network cameras are designed to intimate the real world. For these applications strict requirements of fast, reliable protocol to meet the constraints such as End-to-End delay, maximum packet delivery ratio, goodput. These needs accelerated the emerging of new routing protocols for WSN. Routing protocols are responsible for maintain route, route discovery in the network. And also has responsibility of reliable communication between the multi-hop sensor nodes that may have limited transmission range. In this paper we have surveyed the routing protocols of WSN by splitting the criteria as Multi-path routing, multiple disj oint path routing and single path routing compare the strength and limitations.
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