Distributes award protocol: A cooperation and communication method for robots.

In this Master’s Thesis a new Distributed Award Protocol (DAP) for robot communication and cooperation is presented. Task assignment (contract awarding) is done dynamically with contracts assigned to robots based upon the best bid received. Instead of having a manager and a contractor it is proposed a fully distributed bidding/awarding mechanism without a distinguished master. The best bidding robots are awarded with contract for execution. The contractors make decisions locally. This brings the following benefits: no communication bottleneck, low computational power requirement, increased robustness. DAP can handle multitasking. Tasks can be injected into system during the execution of already allocated tasks. As tasks have priorities, in the next cycle after taking into account actual bid parameters of all robots, tasks can be re-allocated. The aim is to minimize a global cost function which is a compromise between cost of task execution and cost of resources usage. Information about tasks and bid values is spread among robots with the use of a Round Robin Route, which is a novel solution proposed in this work. This method allows also identifying failed robots. Such failed robot is eliminated from the list of awarded robots and its replacement is found so the task is still executed by a team. If the failure of a robot was temporary (e.g. communication noise) and the robot can recover, it can again participate in the next bidding/awarding process. Using a bidding/awarding mechanism allows robots to dynamically relocate among tasks. This is also contributes to system robustness. DAP was evaluated through multiple experiments done in the multi-robot simulation system. Various scenarios were tested to check the idea of the main algorithm. Different failures of robots (communication failures, partial hardware malfunctions) were simulated and observations were made regarding how DAP recovers from them. Also the DAP flexibility to environment changes was watched. The experiments in the simulated environment confirmed the above features of DAP.

Business model with discount incentive in a P2P-cloud multimedia streaming system

Today P2P faces two important challenges: design of mechanisms to encourage users' collaboration in multimedia live streaming services; design of reliable algorithms with QoS provision, to encourage the multimedia providers employ the P2P topology in commercial live streaming systems. We believe that these two challenges are tightly-related and there is much to be done with respect. This paper analyzes the effect of user behavior in a multi-tree P2P overlay and describes a business model based on monetary discount as incentive in a P2P-Cloud multimedia streaming system. We believe a discount model can boost up users' cooperation and loyalty and enhance the overall system integrity and performance. Moreover the model bounds the constraints for a provider's revenue and cost if the P2P system is leveraged on a cloud infrastructure. Our case study shows that a streaming system provider can establish or adapt his business model by applying the described bounds to achieve a good discount-revenue trade-off and promote the system to the users.

A novel monetary incentive for commercial P2P streaming

Today P2P faces two important challenges: design of mechanisms to encourage users’ collaboration in multimedia live streaming services; design of reliable algorithms with QoS provision, to encourage multimedia providers employ the P2P topology in commercial streaming services. We believe that these two challenges are tightly-related and there is much to be done with respect. This paper proposes a novel monetary incentive for P2P multimedia streaming. The incentive model classifies the users in groups according to the perceived video quality. We apply the model to a streaming system’s billing model in order to evaluate its feasibility and visualize its quantitative effect on the users’ motivation and the provider’s profit. We conclude that monetary incentive can boost up users’ cooperation, loyalty and enhance the overall system integrity and performance. Moreover the model defines the constraints for the provider’s cost and profit when the system is leveraged on the cloud. Considering those constraints, a multimedia content provider can adapt the billing model of his streaming service and achieve desirable discount-profit trade-off. This will moreover contribute to better promotion of the service, across the users on the Internet.