1,742 research outputs found
Recommended from our members
Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art
Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP
Distributed and Load-Adaptive Self Configuration in Sensor Networks
Proactive self-configuration is crucial for MANETs such as sensor networks, as these are often deployed in hostile environments and are ad hoc in nature. The dynamic architecture of the network is monitored by exchanging so-called Network State Beacons (NSBs) between key network nodes. The Beacon Exchange rate and the network state define both the time and nature of a proactive action to combat network performance degradation at a time of crisis. It is thus essential to optimize these parameters for the dynamic load profile of the network. This paper presents a novel distributed adaptive optimization Beacon Exchange selection model which considers distributed network load for energy efficient monitoring and proactive reconfiguration of the network. The results show an improvement of 70% in throughput, while maintaining a guaranteed quality-of- service for a small control-traffic overhead
Suboptimal solutions to network team optimization problems
Smoothness of the solutions to network team optimization problems with statistical information structure is investigated. Suboptimal solutions expressed as linear combinations of elements from sets of basis functions containing adjustable parameters are considered. Estimates of their accuracy are derived, for basis functions represented by sinusoids with variable frequencies and phases and
Gaussians with variable centers and widthss
Optimising Network Control Traffic in Resource Constrained MANETS
The exchange of Network State Beacons (NSBs) is crucial to monitoring the dynamic state of MANETs like sensor networks. The rate of beacon exchange (FX) and the network state define both the time and nature of a proactive action to reconfigure the network in order to combat network performance degradation at a time of crisis. It is thus essential to select the FX within optimized bounds, so that minimal control traffic is incurred due to state maintenance and reconfiguration activities. This paper presents a novel distributed model that selects optimized bounds for FX selection and adapts dynamically to the load profile of the network for energy efficient monitoring and proactive reconfiguration
Project Final Report â FREEDOM ICT-248891
This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.This document is the final publishable summary report of the objective and work carried out within the European Project FREEDOM, ICT-248891.Preprin
Context-Awareness Enhances 5G Multi-Access Edge Computing Reliability
The fifth generation (5G) mobile telecommunication network is expected to
support Multi- Access Edge Computing (MEC), which intends to distribute
computation tasks and services from the central cloud to the edge clouds.
Towards ultra-responsive, ultra-reliable and ultra-low-latency MEC services,
the current mobile network security architecture should enable a more
decentralized approach for authentication and authorization processes. This
paper proposes a novel decentralized authentication architecture that supports
flexible and low-cost local authentication with the awareness of context
information of network elements such as user equipment and virtual network
functions. Based on a Markov model for backhaul link quality, as well as a
random walk mobility model with mixed mobility classes and traffic scenarios,
numerical simulations have demonstrated that the proposed approach is able to
achieve a flexible balance between the network operating cost and the MEC
reliability.Comment: Accepted by IEEE Access on Feb. 02, 201
Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting
In a multihop wireless network, it is crucial but challenging to schedule
transmissions in an efficient and fair manner. In this paper, a novel
distributed node scheduling algorithm, called Local Voting, is proposed. This
algorithm tries to semi-equalize the load (defined as the ratio of the queue
length over the number of allocated slots) through slot reallocation based on
local information exchange. The algorithm stems from the finding that the
shortest delivery time or delay is obtained when the load is semi-equalized
throughout the network. In addition, we prove that, with Local Voting, the
network system converges asymptotically towards the optimal scheduling.
Moreover, through extensive simulations, the performance of Local Voting is
further investigated in comparison with several representative scheduling
algorithms from the literature. Simulation results show that the proposed
algorithm achieves better performance than the other distributed algorithms in
terms of average delay, maximum delay, and fairness. Despite being distributed,
the performance of Local Voting is also found to be very close to a centralized
algorithm that is deemed to have the optimal performance
- âŠ