Wirelesssensor Network (WsN) has to diffuse the independent wirelesssensor nodes, which can track the physical or environmental status. In previous works, many issues prevailed with multitask scheduling such as inte...
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Wirelesssensor Network (WsN) has to diffuse the independent wirelesssensor nodes, which can track the physical or environmental status. In previous works, many issues prevailed with multitask scheduling such as interference, high energy consumption, throughput, etc. Moreover, some issues arise while working with heterogeneous WsN. This work deals with these issues in heterogeneous WsN with aid of the multitask scheduling. For this purpose, a Heterogeneous Hybridized Fuzzy-based (depends on degree of truth) Dijkstra's organizing algorithm (HHFDs) was proposed. This technique integrates light weight characteristics as well as a queuing-based analysis methods, hence identifying the greatest parallel arrangements for which the provided data packet effectively. In this technique, fuzzy Dijkstra's algorithm is hybridized with deep neural network. This also depicts in what way to utilize the identifications outcome with varying data packets and thereby helps with various heterogeneous organizing objectives. The proposed HHFDs algorithm is implemented via the use of the network simulator (Ns2). The results of the proposed and existing methods are measured in terms of the metrics like Energy Consumption, Time Consumption, Transmission Delay, and Average Throughput. The simulation results are depicted as follows and the comparison result shown as follows demonstrates the effectiveness of the proposed algorithm.
The goal of this thesis is to explain and implement schoof's algorithm for counting points on elliptic curves over finite fields. We start by defining elliptic curve as a set of pointssatisfying certain equa...
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The goal of this thesis is to explain and implement schoof's algorithm for counting points on elliptic curves over finite fields. We start by defining elliptic curve as a set of pointssatisfying certain equation and then proceeding to define an operation on thisset. Theoretical background needed for the algorithm is presented in the second chapter. Finally, the schoof's algorithm is introduced in the third chapter, supplemented by an implementation in sageMath open-source software.
In general, automobiles travel from the origin to the destination using a shortest route. However, the shortest route may not be a highest wireless connection-capacity route, because of availability of wirelessservic...
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ISBN:
(纸本)9781467309899
In general, automobiles travel from the origin to the destination using a shortest route. However, the shortest route may not be a highest wireless connection-capacity route, because of availability of wirelessservices (base station and access points etc.) along the route. To the best of our knowledge, currently no algorithm exists for selecting a route that maximizes wireless connection-capacity, while keeping route length shortest and close to shortest. In this paper, we propose two modified version of Dijkstra route selection algorithms: one for selecting a maximum connection capacity shortest route, and the other is for discovering higher wireless connection-capacity routes;the length of the route could be larger than a shortest route, but no larger than predetermined bound. The second proposed algorithm exploits the state change of the intersection to broaden the search range of possible routes. Results from our extensive simulation for a Manhattan-street type grid network with the heterogeneous IEEE 802.11a wireless access, show that for a 50% increase in route length and 15 Access Points (APs), the proposed algorithm can increases wireless connection-capacity by 35.67% and 31.27% compared to the shortest and random route selection algorithms, respectively.
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