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Exploring Innovation| ISSN:2319-9598(Online)| Reg. No.:68563/BPL/CE/12| Published by BEIESP| Impact Factor:3.47
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Volume-1 Issue-1: Published on December 20, 2012
42
Volume-1 Issue-1: Published on December 20, 2012

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Volume-1 Issue-1, December 2012, ISSN: 2319-9598 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

K. Sridevi, S. Kannan, S. Karthik

Paper Title:

A Survey on Selfish Node Detection Using Several Techniques in MANET

Abstract: The term MANET (Mobile Ad-hoc Network) refers to a multihop packet based wireless network composed of a set of mobile nodes that can communicate and move at the same time, without using any kind of fixed wired infrastructure. MANET is actually self-organizing and adaptive network that can be formed and deformed on-the-fly without the need of any centralized administration. In practice some of the nodes in MANET act as selfish node that is such kind of nodes reserve their resource and energy for its own use but they do not cooperate with other nodes in the network. This paper discusses several techniques to detect selfish nodes in MANET.

Keywords:
Credit Based, MANET, Reputation Based, Selfish nodes in MANET.


References:

1.        Dipali Koshti and Supriya Kamoji, “Comparative study of    Techniques used for Detection of Selfish Nodes in Mobile Ad hoc Networks”, IJSCE, vol. 1, issue – 4, September 2011.
2.        Khairul Azmi Abu Bakar, “Contribution Time-Based Selfish Node Detection Scheme, 2001.

3.        Prasanna Padmanabhan, Le Gruenwald, Anita Vallur and  Mohammed Atiquzzaman, “A survey of data replication techniques for mobile ad hoc network databases”, the VLDB Journal, 2008.

4.        Pietro Michiardi and Refik Molva, “CORE: A collaborative reputation mechanism to enforce node cooperation in mobile ad hoc networks,” Sixth IFIP conference on security communications, and multimedia (CMS 2002), Portoroz, Slovenia, 2002.

5.        S.Marti, T.Giuli, K.Lai and M.Baker, “Mitigating Routing Misbehavior in Mobile Ad-Hoc Networks,” in Proc. ACM MOBICOM, pp. 25

6.        Sangheethaa Sukumaran , Venkatesh.J and Arunkorah,  “A Survey of Methods to mitigate Selfishness in Mobile Ad hoc Networks”, International JICT, vol. 1, no. 2, June 2011.

7.        Shailender Gupta, Nagpal.C.K. and Charu Singla, “ Impact of Selfish Node Concentration in MANETs”, International Jpurnal of Wireless & Mobile Networks (IJWMN), vol. 3, no.2,April 2011.

8.        Takahiro Hara, “ Effective Replica Allocation in Ad hoc Networks for Improving Data Accessibility, “ IEEE INFOCOM, 2001.

9.        Takahiro Hara, Norishige Murakami and Shojiro Nishio, “Replica Allocation for Correlated Data Items in Ad Hoc Sensor Networks”, SIGMOD Record, vol. 33, no.1, March 2004.

10.     Usha.S, “Multi Hop Acknowledgement Scheme based   Selfish Node Detection in Mobile Ad hoc Networks”, International Journal of Computer and Electrical Engineering, Vol. 3, No. 4, August 2011.

11.     Yang Zhang, “Balancing the Trade-Offs between Query   Delay and Data Availability in MANETs”, IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 4, April 2012.


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2.

Authors:

Dillip Kumar Mahapatra, Tanmaya Kumar Das, Gurudatta Lenka

Paper Title:

Utilizing Virtual Software Teams for Inconsistency Management in Distributed Software Development

Abstract: In the challenging field of software project development, the work is invariably performed by teams. In today’s world of privatization and globalization, where the development costs are increasing at a breakneck speed, the focus is now on cost reduction and availability of highly motivated and suitably trained workforce. Keeping the above mentioned parameters in mind, Companies worldwide are relying on virtual software teams to do the work. This paper highlights the characteristics and throws light on the specifics of virtual software teams. It also illustrates some of the most common issues and challenges that virtual teams face while working on a project there by  exposing some of the ground realities as de scribe the most.

Keywords:
Cohesion, Complexity Factor, CSCW, Cultural Difference, Face-to-Face Interaction, Satisfaction, Socio-Emotional Process, Virtual Team. 


References:

1.        Beise, C., Evaristo, R., & Niederman, F. (2003). Virtual meetings and tasks: from GSS to DGSS to project management. Proceedings of the 36th Annual Hawaii International Conference on System Sciences (str. 9-18). Washington, DC, USA:IEEE Computer Society.
2.        Binder, J. (2007). Global project management: communication, collaboration and management across borders. Aldershot, Hampshire, England: Gower Publishing Ltd.

3.        Biuk-Aghai, R. (2001). Visualizing Structural and Behavioural Aspects of Virtual Collaboration. Tenth IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises. Massachusetts, USA: IEEE.

4.        Brander, E., & Mark, G. (2002). Why Distance Matters: Effects on Cooperation, Persuasion and Deception. CSCW’02 , November 16–20, 226-235.

5.        Brown, B., & Bell, M. (2004). CSCW at play: ‘There’ as a collaborative virtual environment. Proceedings of the 2004 ACM conference on Computer supported cooperative work (str. 350-359). Chicago, Illinois, USA: ACM.

6.        Carmel, E. (1999). Global Software Teams: Collaborating across Borders and Time Zones. Upper Saddle River, NJ: Prentice Hall.

7.        Carmel, E., & Agarwal, R. (2001). Tactical Approaches for Alleviating Distance in Global

8.        Software Development. IEEE Software , March/April 2001, 22-29.

9.        Carstensen, P., & Schmidt, K. (1999). Computer Supported Cooperative Work: New Challenges to Systems Design. U I. Kenji, Handbook of Human Factors. Tokyo.

10.     Powell, A., Piccoli, G. and Ives, B. (2004) Virtual Teams: A Review of Current Literature and Direction for Future Research, The DATA BASE for Advances in Information Systems, 35, 6 - 36.


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