Joint Task Scheduling, Resource Allocation, and UAV Trajectory under Clustering for FANETs

This paper establishes a new layered flying ad hoc networks(FANETs) system of mobile edge computing(MEC) supported by multiple UAVs,where the first layer of user UAVs can perform tasks such as area coverage, and the second layer of MEC UAVs are deployed as flying MEC sever for user UAVs with computing-intensive tasks. In this system, we first divide the user UAVs into multiple clusters, and transmit the tasks of the cluster members(CMs) within a cluster to its cluster head(CH). Then, we need to determine whether each CH’ tasks are executed locally or offloaded to one of the MEC UAVs for remote execution(i.e., task scheduling), and how much resources should be allocated to each CH(i.e., resource allocation), as well as the trajectories of all MEC UAVs.We formulate an optimization problem with the aim of minimizing the overall energy consumption of all user UAVs, under the constraints of task completion deadline and computing resource, which is a mixed integer non-convex problem and hard to solve. We propose an iterative algorithm by applying block coordinate descent methods. To be specific, the task scheduling between CH UAVs and MEC UAVs, computing resource allocation, and MEC UAV trajectory are alternately optimized in each iteration. For the joint task scheduling and computing resource allocation subproblem and MEC UAV trajectory subproblem, we employ branch and bound method and continuous convex approximation technique to solve them,respectively. Extensive simulation results validate the superiority of our proposed approach to several benchmarks.

An Analytical Model for Torus Networks in the Presence of Batch Message Arrivals with Hot-spot Destinations

Interconnection networks are hardware fabrics supporting communications between individual processors in multi- computers. The low-dimensional k-ary n-cubes （or torus） with adaptive wormhole switching have attracted significant research efforts to construct high-performance interconnection networks in contemporary multi-computers. The arrival process and destination distribution of messages have great effects on network performance. With the aim of capturing the characteristics of the realistic traffic pattern and obtaining a deep understanding of the performance behaviour of interconneetion networks, this paper presents an analytical model to investigate the message latency in adaptive-routed wormhole-switched torus networks where there exists hot-spot nodes and the message arrivals follow a batch arrival process. Each generated message has a given probability to be directed to the hot-spot node. The average degree of virtual channel multiplexing is computed by the GE/G/1/V queueing system with finite buffer capacity. We compare analytical results of message latency with those obtained through the simulation experiments in order to validate the accuracy of the derived model.

Editorial: Special issue on blockchain and communication networks

1.Introduction With the boom of new technologies and applications,e.g.,Internet of Things,big data,and artificial intelligence,a deluge of devices are being connected to the network,thus generating a large amount of data[1].Data collection,processing and analysis are essentials to help people gain valuable information,make sensible decisions,and also make devices intelligent.The underlying communication network is thus facing unprecedented challenges.Along with the increase in devices,managing these devices in the existing centralized model will bring significant challenges to the infrastructure construction,maintenance,and management of the communication network.In addition,the current technology/protocol in communication networks cannot adequately ensure the security and privacy of user data,and the use of collected data is beyond the control of the user.Internet users and companies,therefore,are concerned for the privacy of their data,unwilling to provide valuable data for processing and analysis.

Guest editorial:Blockchain-enabled technologies for cyber-physical systems and big data applications

1.Background and motivation Cyber-Physical System(CPS)refers to the seamless integration of the physical processes,computational components,and Internet-of-Things(IoT)devices such as sensors,actuators,and so on.Examples of CPS include smart grids,autonomous transportation systems,medical monitoring,process control systems,robotic systems,and automatic pilot avionics.