Smart grids (SG) require data compression and encryption algorithms to communicate large amount of data in the secure way. However, existing algorithms are not appropriate for smart grid as they consume huge memory an...
详细信息
Smart grids (SG) require data compression and encryption algorithms to communicate large amount of data in the secure way. However, existing algorithms are not appropriate for smart grid as they consume huge memory and take significant amount of execution time. Consequently, we explored other algorithms and choose the neighbourhood indexing sequence algorithm (NIS) for data compression and the PICO algorithm for cryptography. Further, PICO algorithm is enhanced in two ways. Firstly, random bits are generated and added to the plaintext to increase the block size that improves the security of the algorithm. The random bits are generated by hybrid of cuckoo search and genetic algorithm. Secondly, software optimisation algorithms namely loop unrolling and binary search algorithms are used to reduce execution time. The experimental results demonstrate the better performance of proposed algorithm EPICO over PICO in terms of memory consumption, execution time, correlation coefficient and avalanche effect.
Wireless Sensor Networks play a crucial role in everyday life, providing a wide range of networking structures to develop real-time applications. Energy consumption is limited by WSN devices, so reducing the energy co...
详细信息
Wireless Sensor Networks play a crucial role in everyday life, providing a wide range of networking structures to develop real-time applications. Energy consumption is limited by WSN devices, so reducing the energy consumption of malicious nodes is crucial to improving network performance. A main concern of WSNs from an application perspective is the prolonged lifetime of the network and reduced energy usage. To overcome these challenges a novel multi-objective ED2MT (Energy, Distance, Degree, Mobility, Time) driven strategy has been proposed which consists of three phases namely dual Cluster Head Selection, data compression, and routing. In the first phase, the proposed ED2MT uses a Fuzzy C-Means (FCM) clustering algorithm to select dual Cluster Head (CH) which has been performed in two stages, namely Inter-Cluster and Intra-Cluster. In the second phase, a Neighborhood indexingsequence (NIS) technique is utilized to compress the number of bits in the data before it is transmitted. In the third phase, a multi-objective shortest-path routing algorithm is utilized for route selection. The performance of the ED2MT method has been evaluated using network lifetime, delay, throughput, alive nodes, energy efficiency, and packet delivery ratio to provide a better result. The proposed ED2MT framework achieves 20.55%, 18.4%, and 15.2% more residual energy than C3HA, CAFL, and DHSCA algorithms.
暂无评论