Advanced Computing, Networking and Informatics- Volume 2: by Malay Kumar Kundu, Durga Prasad Mohapatra, Amit Konar, Aruna

By Malay Kumar Kundu, Durga Prasad Mohapatra, Amit Konar, Aruna Chakraborty

Advanced Computing, Networking and Informatics are 3 precise and at the same time particular disciplines of data with out obvious sharing/overlap between them. although, their convergence is saw in lots of genuine global functions, together with cyber-security, net banking, healthcare, sensor networks, cognitive radio, pervasive computing amidst many others. This two-volume lawsuits discover the mixed use of complicated Computing and Informatics within the subsequent iteration instant networks and safeguard, sign and snapshot processing, ontology and human-computer interfaces (HCI). the 2 volumes jointly contain 148 scholarly papers, which were approved for presentation from over 640 submissions within the moment foreign convention on complex Computing, Networking and Informatics, 2014, held in Kolkata, India in the course of June 24-26, 2014. the 1st quantity contains cutting edge computing strategies and proper learn leads to informatics with selective purposes in development attractiveness, signal/image processing and HCI. the second one quantity nonetheless demonstrates the prospective scope of the computing suggestions and informatics in instant communications, networking and security.

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Extra info for Advanced Computing, Networking and Informatics- Volume 2: Wireless Networks and Security Proceedings of the Second International Conference on Advanced Computing, Networking and Informatics (ICACNI-2014)

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7. Next we scan Lx and include si (if Lx = ai ), or delete si (if Lx = bi ) in L and compute intersections among the newly adjacent Fast Estimation of Coverage Area in a Pervasive Computing Environment 23 Algorithm 1. Intersection(s,¯ s, P (s), P (¯ s)) Input: s = (x1 , x2 , y1 , y2 ), s ¯ = (¯ x1 , x ¯2 , y¯1 , y¯2 ), P (s) : (p1 , p2 , p3 , p4 ), P (¯ s) : (p¯1 , p ¯2 , p¯3 , p¯4 ) Output: P (s), P (¯ s) if y1 == y¯1 then if p1 ≤ x ¯1 and p2 ≥ x ¯1 then p2 = x ¯1 ; ¯1 and p4 ≥ x ¯1 then p4 = x ¯1 ; if p3 ≤ x if x1 == x ¯1 then if y1 > y¯1 then p¯1 = p¯2 = p3 = p4 = null ; else p1 = p2 = p¯3 = p¯4 = null; if y¯1 > y1 then if p1 ≤ x ¯1 and if p¯3 ≤ x2 and else if p3 ≤ x ¯1 and if p¯1 ≤ x2 and p2 ≥ x ¯1 then p2 = x ¯1 ; p¯4 ≥ x2 then p¯3 = x2 ; p4 ≥ x ¯1 then p4 = x ¯1 ; p¯2 ≥ x2 then p¯1 = x2 ; p1 (s3 ) s3 p1 (s1 ) + b1 p4 (s4 ) p3 (s4 ) p3 (s1 ) a2 a3 + + s2 a1 p2 (s4 ) p2 (s1 ) s4 s1 y p2 (s3 ) p1 (s4 ) a4 b2 b3 b4 x Fig.

Section 3 describes the algorithms for finding the intersection points and the area covered by squares. Section 4 shows the simulation results and finally Section 5 concludes the paper. 2 Problem Formulation Let a set of n nodes S = {s1 , s2 , . . , sn } be deployed randomly over a 2-D region A. Each node covers a circular area with radius r. The problem is to decide whether the region A is fully covered by the nodes. Note that a computation considering real circles in Euclidean geometry is rather complex.

Unexpected faults may arise in unreliable networks. Then it is not a good approach to create fault tolerance mechanism for every one of them. A unique solution may be created an adaptive mechanism to deal with several types of faults. Chameleon is one of such mechanism for fault tolerance [13]. Flexibility of chameleon gives it its advantage in the case of unreliable networks. The disadvantage of this mechanism is that it becomes blocking if execution at any node fails. Exactly once protocol guarantees fault less execution in case where the agent needs to be executed only once to yield a correct result, executing more than once may lead to errors.

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