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For over a decade, the Nash bargaining solution (NBS) concept from cooperative game theory has been used in networks to share resources fairly. Due to its many appealing properties, it has recently been used for assigning bandwidth in a general topology network between applications that have linear utility functions. In this paper, we use this concept for(More)
— Recent mobile equipment (as well as the norm IEEE 802.21) offers the possibility for users to switch from one technology to another (vertical handover). This allows flexibility in resource assignments and, consequently, increases the potential throughput allocated to each user. In this paper, we design a fully distributed algorithm based on trial and(More)
— In third generation mobile networks, transmission rates can be assigned to both real time and non real time applications. We address in this paper the question of how to allocate transmission rates in a manner that is both optimal and fair. As optimality criterion we use the Pareto optimality notion, and as fairness criterion we use a general concept of(More)
Various fairness objectives are studied in relation to Pareto optimal sets and Nash equilibria. We examine the already discussed general parameterized fairness objective that covers a variety of fairness criteria and the newly introduced Nash-proportionate-fairness objective. We study them mainly numerically on a simple static load balancing model with two(More)
This paper presents an algorithm for resource allocation in satellite networks. It deals with planning a time/frequency plan for a set of terminals with a known geometric configuration under interference constraints. Our objective is to maximize the system throughput while guaranteeing that the different types of demands are satisfied, each type using a(More)
In this paper, we present a fully decentralized algorithm for fair resource sharing between multiple bag-of-tasks applications in a grid environment. This algorithm is inspired from related work on multi-path routing in communication network. An interesting feature of this algorithm is that it allows the choice of wide variety of fairness criteria and(More)
Multiple applications that execute concurrently on heterogeneous platforms compete for CPU and network resources. In this paper we analyze the behavior of K non-cooperative schedulers using the optimal strategy that maximize their efficiency while fairness is ensured at a system level ignoring applications characteristics. We limit our study to simple(More)
There are several approaches of sharing resources among users. There is a noncooperative approach wherein each user strives to maximize its own utility. The most common optimality notion is then the Nash equilibrium. Nash equilibria are generally Pareto inefficient. On the other hand, we consider a Nash equilibrium to be fair as it is defined in a context(More)