1,721,239 research outputs found
Age-Oriented Resource Allocation for IoT Computational Intensive Tasks in Edge Computing Systems
No full textCurrent edge computing (EC) solutions face the significant challenge of limited computational capacities. Effectively allocating resources and controlling the system to ensure task timeliness remains an open problem. The age of information (AoI) is a metric to measure the freshness of information that circulates in a system. While the AoI is primarily influenced by packet generation rate, transmission latency, and queuing delays, the processing time becomes notably significant when dealing with Internet-of-Things (IoT) computationally intensive tasks. Such IoT applications necessitate processing before embedded information can emerge and status can be acquired. This paper proposes a combined system control and resource assignment policy, in new-generation EC environments, where edge nodes have limited capacity and task flows are computationally intensive. The objective is to assign task flows to dedicated resource capacity, minimizing the worst AoI experienced by flows. For this purpose, three problem formulations for the flow-resource assignment are considered: i) the assignment with fixed arrival and service processes; ii) the service process control problem; iii) the arrival process control problem. For each problem formulated, a matching game with externalities is designed, and preference lists are built considering the mean AoI of an M/G/1 system, here exploited as reference model to represent each computation partition. The stability of matching games proposed is investigated, and experimental results are presented to highlight the validity of the matching approaches, providing critical discussion about the performance impact of the three problems addressed, also compared with a reservoir learning approach. The proposed matching algorithm surpasses the state-of-the-art Deferred Acceptance method by achieving a lower maximum AoI, thereby meeting the optimization objective. It also demonstrates improved performance over the data-driven approach. While comparable maximum AoI values can be attained with sufficiently large training datasets, the proposed algorithm consistently yields superior results
Performance Evaluation Of HIPERLAN/2 Bandwidth Allocation Mechanisms With Different Types Of Traffic
No full text
Scheduling method and apparatus for half-duplex transmission
No full textThe present invention relates to a method and apparatus for scheduling data for transmission via at least two half-duplex time division multiple access connections, wherein for each connection respective capacities of data portions to a transmission frame are allocated so that the total capacity of all data portions of the transmission frame does not exceed a predetermined capacity for each transmission direction, and that the sum of capacities of data portions of each connection of the transmission frame in both transmission directions does not exceed the predetermined capacity. Then, the transmission timing of the data portions within the transmission frame is set in such a manner that transmission and reception intervals of each connection do not overlap. Accordingly, scheduling can be optimized to meet both QoS and half-duplex requirements
Data transmission method, system, base station and subscriber station, a data processing unit, computer program product, computer program distribution medium and baseband module
No full textA data transmission method in a communication system including transmitting at least one capacity request message from a subscriber station, granting capacity subscriber station-specific by a base station, transmitting at least one capacity grant message from the base station, allocating granted capacity connection-specific by the subscriber station, transmitting from the subscriber station at least one message, which includes information on previous capacity requests, transmitting data from the subscriber station according to capacity allocation, monitoring by the base station request messages, capacity grant messages and received transmissions
Efficient design of wireless mesh networks with robust dynamic frequency selection capability
No full textWireless Mesh Networks (WMN) operating in the 5 GHz band must implement Dynamic Frequency Selection (DFS) capabilities to cope with the presence of radar systems operating in the same frequencies. In particular, upon detection of a radar event, WMN devices must switch to a different channel within a given time specified by radio regulations. This is not only mandatory to avoid interference to radar systems, but is also convenient since radar pulses are a source of interference to the WMN itself. In this work we propose a solution for the deployment of WMNs using channels co-located with radar systems in an efficient and reliable manner. Our contribution is two-fold. First, we specify a distributed coordinated channel change procedure which reacts efficiently to radar events. We then formulate an optimization problem to find the best channel allocation which explicitly takes DFS into account, and provide a heuristic algorithm to solve it. We assess the proposed approach numerically and by simulation. Evaluation results motivate our work by confirming that DFS, which has been disregarded in previous work on WMN channel assignment, may have a significant impact on the performance of the network, and show that our solution is effective in finding a good trade-off between channel spatial reuse and DFS management
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