Imola: A decentralised learning-driven protocol for multi-hop White-Fi

In this paper we tackle the digital exclusion problem in developing and remote locations by proposing Imola, an inexpensive learning-driven access mechanism for multi-hop wireless networks that operate across TV white-spaces (TVWS). Stations running Imola only rely on passively acquired neighbourhood information to achieve scheduled-like operation in a decentralised way, without explicit synchronisation. Our design overcomes pathological circumstances such as hidden and exposed terminals that arise due to carrier sensing and are exceptionally problematic in low frequency bands. We present a prototype implementation of our proposal and conduct experiments in a real test bed, which confirms the practical feasibility of deploying our solution in mesh networks that build upon the IEEE 802.11af standard. Finally, the extensive system level simulations we perform demonstrate that Imola achieves up to 4x\u97 more throughput than the channel access protocol defined by the standard and reduces frame loss rate by up to 100%

Practical Evaluation of Low-complexity Medium Access Control Protocols for Wireless Sensor Networks

This thesis studies the potential of a novel approach to ensure more efficient and intelligent assignment of capacity through medium access control (MAC) in practical wireless sensor networks (WSNs), whereby Reinforcement Learning (RL) is employed as an intelligent transmission strategy. RL is applied to framed slotted-ALOHA to provide perfect scheduling. The system converges to a steady state of a unique transmission slot assigned per node in single-hop and multi-hop communication if there is sufficient number of slots available in the network, thereby achieving the optimum performance. The stability of the system against possible changes in the environment and changing channel conditions is studied. A Markov model is provided to represent the learning behaviour, which is also used to predict how the system loses its operation after convergence. Novel schemes are proposed to protect the lifetime of the system when the environment and channel conditions are insufficient to maintain the operation of the system. Taking real sensor platform architectures into consideration, the practicality of MAC protocols for WSNs must be considered based on hardware limitations/constraints. Therefore, the performance of the schemes developed is demonstrated through extensive simulations and evaluations in various test-beds. Practical evaluations show that RL-based schemes provide a high level of flexibility for hardware implementation

A Learning Approach to Decentralised Beacon Scheduling

Accepted for publication in Elsevier Ad-Hoc NetworksBeaconing is usually employed to allow network discovery and to maintain synchronisation in mesh networking protocols, such as those defined in the IEEE 802.15.4e and IEEE 802.11s standards. Thus, avoiding persistent or consecutive collisions of beacons is crucial in order to ensure correct network operation. Beacons are also used in receiver-initiated medium access protocols to advertise that nodes are awake. Consequently, effective beacon scheduling can enable duty-cycle operation and reduce energy consumption. In this work, we propose a completely decentralised and low-complexity solution based on learning techniques to schedule beacon transmissions in mesh networks. We show the algorithm converges to beacon collision-free operation almost surely in finite time and evaluate converge times in different mesh network scenarios

Genetic algorithms for satellite scheduling problems

Recently there has been a growing interest in mission operations scheduling problem. The problem, in a variety of formulations, arises in management of satellite/space missions requiring efficient allocation of user requests to make possible the communication between operations teams and spacecraft systems. Not only large space agencies, such as ESA (European Space Agency) and NASA, but also smaller research institutions and universities can establish nowadays their satellite mission, and thus need intelligent systems to automate the allocation of ground station services to space missions. In this paper, we present some relevant formulations of the satellite scheduling viewed as a family of problems and identify various forms of optimization objectives. The main complexities, due highly constrained nature, windows accessibility and visibility, multi-objectives and conflicting objectives are examined. Then, we discuss the resolution of the problem through different heuristic methods. In particular, we focus on the version of ground station scheduling, for which we present computational results obtained with Genetic Algorithms using the STK simulation toolkit.Peer ReviewedPostprint (published version

A Survey of Scheduling in 5G URLLC and Outlook for Emerging 6G Systems

Future wireless communication is expected to be a paradigm shift from three basic service requirements of 5th Generation (5G) including enhanced Mobile Broadband (eMBB), Ultra Reliable and Low Latency communication (URLLC) and the massive Machine Type Communication (mMTC). Integration of the three heterogeneous services into a single system is a challenging task. The integration includes several design issues including scheduling network resources with various services. Specially, scheduling the URLLC packets with eMBB and mMTC packets need more attention as it is a promising service of 5G and beyond systems. It needs to meet stringent Quality of Service (QoS) requirements and is used in time-critical applications. Thus through understanding of packet scheduling issues in existing system and potential future challenges is necessary. This paper surveys the potential works that addresses the packet scheduling algorithms for 5G and beyond systems in recent years. It provides state of the art review covering three main perspectives such as decentralised, centralised and joint scheduling techniques. The conventional decentralised algorithms are discussed first followed by the centralised algorithms with specific focus on single and multi-connected network perspective. Joint scheduling algorithms are also discussed in details. In order to provide an in-depth understanding of the key scheduling approaches, the performances of some prominent scheduling algorithms are evaluated and analysed. This paper also provides an insight into the potential challenges and future research directions from the scheduling perspective