Optimal Task Offloading Policy in Discrete-Time Systems with Firm Deadlines

The recent drastic increase in mobile data traffic has pushed the mobile edge computing systems to the limit of their capacity. A promising solution to this problem is the task migration provided by unmanned aerial vehicles (UAV). Key factors to be taken into account in the design of UAV offloading schemes must include the number of tasks waiting in the system as well as their corresponding deadlines. An appropriate system cost which is used as an objective function to be minimized comprises two parts. First, an offloading cost which can be interpreted as the cost of using computational resources at the UAV. Second, a penalty cost due to potential task expiration. In order to minimize the expected (time average) cost over a time horizon, we formulate a Dynamic Programming (DP) equation and analyze it to describe properties of a candidate optimal offloading policy. The DP equation suffers from the well-known "Curse of Dimensionality" that makes computations intractable, especially when the state space is infinite. In order to reduce the computational burden, we identify three important properties of the optimal policy. Based on these properties, we show that it suffices to evaluate the DP equation on a finite subset of the state space only. We then show that the optimal task offloading decision associated with a state can be inferred from the decision taken at its "adjacent" states, further reducing the computational load. Finally, we provide numerical results to evaluate the influence of different parameters on the system performance as well as verify the theoretical results

Towards Multi-Service Traffic Shaping in Two-Tier Enterprise Data Centers

International audienceIn Enterprise Data Centers (EDC), service providers are usually governed by Client Service Contracts (CSC) that specify, among other requirements, the rate at which a service should be accessed. The contract limits the rate to no more than a number of service requests during a given observation period. In two-tier setups, a cluster of Service-Oriented Networking (SON) Appliances form a pre-processing tier that accesses services in the service tier. SON Appliances locally shape the flow of requests to enforce the global rate defined in the CSC. Off-the-shelf SON Appliances present architectural limitations that prevent them from being used to efficiently perform traffic shaping in the presence of multiple service hosts. In this paper, besides identifying these limitations, we provide two contributions in this field. First, we introduce a SON Appliance architecture fit for multi-service traffic shaping. Second, we propose and validate an algorithm for multipoint-to-multipoint service traffic shaping in two-tier EDCs. We show via simulation that our approach solves the multipoint-to-multipoint service traffic shaping problem while pushing the system to its maximum capacity

Experiments in Hybrid Networking with the Advanced Communications Technology Satellite

This paper describes experiments conducted over ACTS that were motivated by the commercial potential of low-cost receive-only satellite terminals operating in a hybrid network environment. The first experiment tested highly adaptive methods of satellite bandwidth allocation in an integrated voice-data service environment. The second involved comparison of FEC and ARQ methods of error control for satellite communication with emphasis on the advantage that a hybrid architecture provides especially in the case of multicasts. Finally, the third experiment demonstrated hybrid access to databases through the use of Mosaic and compared the performance of internetworking protocols for interconnecting LANs via satellite

Dynamic Service Contract Enforcement in Service-Oriented Networks

International audienceIn recent years, Service Oriented Architectures (SOA) have emerged as the main solution for the integration of legacy systems with new technologies in the enterprise world. A service is usually governed by a client service contract (CSC) that specifies, among other requirements, the rate at which a service should be accessed, and limits it to no more than a number of service requests during an observation period. Several approaches, using both static and dynamic, credit-based strategies, have been developed in order to enforce the rate specified in the CSC. Existing approaches have problems related to starvation, approximations used in calculations, and rapid credit consumption under certain conditions. In this paper, we propose and validate DoWSS, a doubly-weighted algorithm for service traffic shaping. We show via simulation that DoWSS possesses several advantages: it eliminates the approximation issues, prevents starvation and contains the rapid credit consumption issue in existing credit-based approaches

Extension of the Optimality of the Threshold Policy in Heterogeneous Multiserver Queueing Systems.

We extend the validity of some results on the optimal control of two-server queueing models with service times of unequal distribution, operating in continuous or discrete time. The distribution of arrivals can be arbitrarily subject to some conditions. Both discounted and long run average costs are considered. Dynamic programming and probabilistic arguments are the key tools used to establish the assertion that the optimal policy is of threshold type, i.e. the slower server should be utilized only when the queue length exceeds a certain threshold value