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Abstract-Insufficiency of memory and battery power of sensors makes the security of sensor networks a hard task to do. This insufficiency also makes applying the existing methods of securing other type of networks on the sensor networks unsuitable. We propose a game theoretic framework for defensing nodes in a sensor network. We apply three different schemes for defense. Our main concern in all three schemes is finding the most vulnerable node in a sensor network and protecting it. In the first scheme we formulate attack-defense problem as a two-player, nonzero-sum, non-cooperative game between an attacker and a sensor network. We show that this game achieves Nash equilibrium and thus leading to a defense strategy for the network. In the second scheme we use Markov Decision Process to predict the most vulnerable senor node. In the third scheme we use an intuitive metric (node's traffic) and protect the node with the highest value of this metric. We evaluate the performance of each of these three schemes, and show that the proposed game framework significantly increases the chance of success in defense strategy for sensor network.

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This paper realizes the vision of Mobile Grid Computing by proposing a fair pricing strategy and an optimal, static job allocation scheme. Mobile devices has not yet been integrated into Grid computing platforms mainly due to their inherent limitations in processing and storage capacity, power and bandwidth shortages. However, millions of laptops, PDAs and other mobile devices remain unused most of the time and this huge resource repository can be potentially utilized in the Grid environment. Here, we propose a game theoretic pricing model, to address load balancing issues in mobile grids. In particular, by drawing upon the Nash Bargaining Solution (NBS), we show that we can obtain a unified framework for addressing such issues as network efficiency, fairness, utility maximization, and pricing. The advantage of this framework is that we have a precise mathematical characterization of the solutions and their properties. Our current endeavor characterizes a twoplayer alternating-offer bargaining game between the Wireless Access Point (WAP) Server and the mobile devices to determine the pricing strategy which is then used to effectively distribute jobs to the mobile devices. Our job allocation scheme maximizes the revenue of the grid user, and yet is comparable to other load balancing schemes in terms of the overall system response time.