The mixture-of-experts model is a static neural network architecture in that it learns input-output mappings where the output is directly influenced by the current input but not previous inputs. We explore a dynamic version of the mixture-of-experts model by introducing feedback into the architecture, enabling it to learn temporal behaviour. The model’s ability to decompose a task into static a...

Growing processing demand on multi-tasking real-time systems can be met by employing scalable multicore architectures. For such environments, locking cache lines for hard real-time systems ensures timing predictability of data references and may lower worst-case execution time. This work studies the benefits of cache locking on massive multicore architectures with private caches in the context ...

Current processor allocation techniques for highly parallel systems are based on centralized front-end based algorithms. As a result, the applied strategies are restricted to static allocation, low parallelism and weak fault tolerance. To lift these restrictions we are investigating a distributed approach to the processor allocation problem in large meshconnected multicomputers. A noncontiguous...

Task allocation is an issue that every multi-robot system must address. Recent task allocation solutions propose an auction based approach wherein robots bid for tasks based on cost functions for performing a task. This paper presents RACHNA, a novel architecture for multi-robot task allocation based on a modified algorithm for the winner determination problem in multi-unit combinatorial auctio...

The sharing of resources among processes in a distributed system leads to a connict graph that may change with time. Resource allocation over a static connict graph (also called the dining philosophers problem) has been studied extensively. We seek to solve resource allocation on dynamic connict graphs by using existing algorithms that work only for static connict graphs. In the process we deen...

In this paper, we propose a new subcarrier allocation algorithm for a downlink OFDMA relay network with multicells. In the proposed algorithm, subcarriers are allocated to users and relays to maximize the overall sum of the achievable rate under fairness constraints. Simulation results show that the proposed algorithm achieves higher data rate than the static algorithm and reduces the outage pr...

Incorporating mobile-edge computing (MEC) in the Internet of Things (IoT) enables resource-limited IoT devices to offload their computation tasks a nearby edge server. In this article, we investigate an system assisted by MEC technique with its task subjected sequential dependency, which is critical for video stream processing and other intelligent applications. To minimize energy consumption p...

Task allocation for heterogeneous agents in disaster environments under time, space and communication constraints is a challenging issue in both theory and practice. This paper presents a dynamic task allocation approach for such situations. The proposed approach consists of an information collection mechanism, a group task allocation mechanism and a group coordination mechanism. Initially, the...

By offloading computationally intensive tasks of smart end devices to edge servers deployed at the network, mobile computing (MEC) has become a promising technology provide services for Internet Things (IoT) devices. In order further improve access capability MEC and increase spectrum utilization efficiency, in this article, Non-Orthogonal Multiple Access (NOMA) is introduced into systems we st...