Node cooperation during packet forwarding operations is critically important for fair resource utilization in Community Wireless Mesh Networks (CoWMNs). In a CoWMN, node cooperation is achieved by using fairness protocols specifically designed to detect and isolate malicious nodes, discourage unfair behavior, and encourage node participation in forwarding packets. In general, these protocols ca...

Most R&D projects are executed by employing teams of researchers and in distinct phases. These two features distinguish the agency problem that a firm faces with respect to its inhouse R&D unit from traditional principal-agent problems. This paper analyzes this agency problem by studying a continuous-time multi-agent incentive problem in which a principal hires two risk-averse agents to perform...

The prime focus of this study is in developing distributed algorithms for cognitive relaying with time incentive for multiple primary users (CRTI-M). CRTI-M is a symbiotic paradigm in which the incumbent primary users (PUs) of the spectrum, with weak transmission links, seek cooperation from the cognitive secondary user (SU) nodes in their vicinity, and in return reward them with an incentive t...

A model is constructed in which consumers and banks have incentives to fake the quality of collateral. Conventional monetary easing can exacerbate these problems, in that the mispresentation of collateral becomes more profitable, thus increasing haircuts and interest rate differentials. Central bank purchases of private mortgages may not be feasible, due to misrepresentation of asset quality. I...

Wireless Ad-hoc networks are expected to be made up of energy aware entities (nodes) interested in their own perceived performance. We consider a simple random access model for a wireless ad hoc network to address problems of finding an optimal channel access rate and providing incentive for cooperation to forward other nodes’ traffic. By casting these problems as noncooperative games, we deriv...

We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of revenue-maximizing pricing problems. Our reductions imply that for these problems, given an optimal (or β-approximation) algorithm for an algorithmic pricing problem, we can convert it into a (1 + )-approximation (or β(1...

We study cost-sharing mechanisms for several fundamental NP-hard combinatorial optimization problems. A cost-sharing mechanism is a protocol that, given bids for a service, determines which bidders to serve and what prices to charge. The mechanism incurs a subset-dependent cost that is implicitly defined by an instance of a combinatorial optimization problem. Three desirable but mutually incomp...

To a large extent the present work is far from being conclusive, instead, new directions of research in combinatorial extremal theory are started. Also questions concerning generalizations are immediately noticeable. The incentive came from problems in several fields such as Algebra, Geometry, Probability, Information and Complexity Theory. Like several basic combinatorial problems they may pla...