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The wireless sensor networks and manage the wireless communication, whereas MASs allow distributed systems to be designed and implemented in an autonomous way by optimizing the development process. Using autonomous objects provides new mechanisms for efficient processor and memory usage while enabling low-power consumption in communication. We have presented a content-based networking protocol to solve some inherent problems in wireless sensor networks, especially in communication. Content-based protocols are mainly maximized the rate of suitable message delivery and minimize the energy consumption by using techniques to maintain shortest paths. The proposed protocol sends data using agent-based platform, and each sensor can make its decision individually. This mechanism prolongs life time of the network. After some nodes die, system can automatically construct new paths for data dissemination. In this work, proposed model for security in wsn using Homomorphic encryption. As an experimental work, the performance analysis and evaluations are conducted in terms of some main efficiency metrics, which are first node dies and half of the nodes alive. As an energy-aware system, the total remaining energy level also be calculated, and this metric can be used for estimating the lifetime of the system.


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P. A. K. Acharya, A. Sharma, E. M. Belding, K. C. Almeroth, S. Member, and D. Papagiannaki, “Rate adaptation in congested wireless networks through real-time measurements,†IEEE Transactions on Mobile Computing, vol. 9, no. 11, pp. 1535–1550, Nov. 2010.

Y. Sheng, G. Chen, H. Yin, K. Tan, U. Deshpande, B. Vance, D. Kotz, A. Campbell, C. McDonald, T. Henderson, and J. Wright, “MAP: a scalable monitoring system for dependable 802.11 wireless networks,†Wireless Communications, IEEE, vol. 15, no. 5, pp.10–18, October.

.K. Tan, C. McDonald, B. Vance, C. Arackaparambil, S. Bratus, and D. Kotz, “From MAP to DIST: the evolution of a largescale WLAN monitoring system,†IEEE Transactions on Mobile Computing, vol. 99, no. PrePrints, p. 1, 2012.

MatteoSammarco, Miguel Elias M. Campista, and Marcelo Dias de Amorim “Scalable Wireless Traffic Capture Through Community Detection and Trace Similarity†in IEEE TRANSACTIONS ON MOBILE COMPUTING vol.15, issue July 2016

U. N. Raghavan, R. Albert, and S. Kumara, “Near linear time algorithm to detect community structures in large-scale networks,†Physical Review E, vol. 76, no. 3, pp. 036 106+, Sep. 2007.

A. Argyriou and V. Madisetti, “Using a New Protocol to Enhance Path Reliability and Realize Load Balancing in Mobile Ad Hoc Networks,†Ad Hoc Networks, vol. 4, pp. 60-74, 2006.

A, Bletsas, A. Khisti, D.P. Reed, and A,Lippman, “A Simple Cooperative Diversity Method Based on Network Path Selection,†IEEE J. Selected Areas in Comm., vol. 24, no. 3, pp. 659-672, Mar. 2006.

V. Venkataramanan, X. Lin, L. Ying, and S. Shakkottai, “On Scheduling for Minimizing End-to-End Buffer Usage over Multi- Hop Wireless Networks,†Proc. IEEE INFOCOM, 2010.

B. B. Romdhanne, D. Dujovne, and T. Turletti, “Efficient and scalable merging algorithms for wireless traces,†in Workshop on Real Overlays and Distributed Systems (ROADS), Oct. 2009, pp. 1–7.

A. Balachandran, G. M. Voelker, P. Bahl, and P. V. Rangan, “Characterizing user behavior and network performance in a public wireless LAN,†in ACM SIGMETRICS, Jun.15-19 2002, pp. 195–205.

M. Sammarco, M. E. M. Campista, and M. D. de Amorim, “Trace selection for improved WLAN monitoring,†in ACM HotPlanet Workshop, Aug.16 2013, pp. 1–6.

M. E. J. Newman and M. Girvan, “Finding and evaluating community structure in networks,†Physical Review E, vol. 69, no. 2, pp. 026 113+, Feb. 2004.