In Wireless Sensor Networks, mobile sensing refers to the presence of one or more mobile sinks or mobile sensors, which have the main role of collecting the gathered data by sensor nodes. This paper describes a new scheme of mobile sensing that aims at providing a good coverage and throughput while maintaining better energy efficiency and high network availability. To achieve this, some features of the social foraging behavior of the Escherichia coli bacteria have been used, especially the chemotaxis and swarming processes that allow bacteria to move. Particularly, a description and a formulation of a mobile sensing scheme based on an approach inspired by the Bacterial Foraging Optimization have been provided. Models that allow mobile sinks to move over the network in a self-organized and self-adaptive way have been proposed. The proposal has been experimented in order to elaborate the impact of mobility on delay, network coverage and successful amount of collected data. The obtained results demonstrate the effectiveness of the proposal.

Nowadays, enterprises can provide computing services through their intranet networks by letting their available resources be used as virtual clusters for scientific computation during idle periods such as nights, weekends, and holidays. Generally, these idle periods do not permit to carry out the computations completely. It is therefore necessary to save the context of uncompleted applications for possible restart. This checkpointing mechanism is subject to resource constraints: the network bandwidth, the disk bandwidth, and the delay T imposed for releasing the workstations. We first introduce a function bw that gives the bandwidth bw(m,V) of a system during the checkpointing of m applications with aggregated memory requirement V. Assuming that this bandwidth is shared equitably among the applications, the scheduling problem becomes a sequence of knapsack problems with nonlinear constraints for which we propose approximate solutions. Experiments carried out on Grid5000 show that the running time of this algorithm is negligible compared to the delay T which is of the order of few minutes. This means that the proposed scheduling algorithm does not induce a significant overhead on the checkpointing process. As a consequence, our mechanism can be incorporated in a batch scheduler.

We consider a context where the available resources of the Intranet of a company are used as a virtual cluster for scientific computation, during the idle periods (nights, weekends, holidays, ). Generally, these idle periods do not permit to carry out completely the computations. For instance, a workstation mobilized during the night must be released in the morning to make it available for the employee, even if the application running on it is not completed. It is therefore necessary to save the context of uncompleted applications for possible restart. Hereafter, we assume that the computations running on the workstations are independent from each other. The checkpointing mechanism which ensures the continuity of applications is subject to resource constraints : the network bandwidth, the disk bandwidth and the delay T imposed for releasing the workstations. We first show that the designing of a scheduling strategy which optimizes resource consumption while taking into account the above constraints, can be formalized as a variant of the classical 0/1 knapsack problem. We then propose an algorithm whose implementation does not have a significant overhead on checkpointing mechanisms. Experiments carried out on a real cluster show that this algorithm performs better than the naive scheduling algorithm which selects the applications one after the other in order of decreasing amount of resource consumption.