Cross-layer signalling and middleware: a survey for inelastic soft real-time applications in MANETs

This paper provides a review of the different cross-layer design and protocol tuning approaches that may be used to meet a growing need to support inelastic soft real-time streams in MANETs. These streams are characterised by critical timing and throughput requirements and low packet loss tolerance levels. Many cross-layer approaches exist either for provision of QoS to soft real-time streams in static wireless networks or to improve the performance of real and non-real-time transmissions in MANETs. The common ground and lessons learned from these approaches, with a view to the potential provision of much needed support to real-time applications in MANETs, is therefore discussed

Layering as Optimization Decomposition: Questions and Answers

Network protocols in layered architectures have historically been obtained on an ad-hoc basis, and much of the recent cross-layer designs are conducted through piecemeal approaches. Network protocols may instead be holistically analyzed and systematically designed as distributed solutions to some global optimization problems in the form of generalized Network Utility Maximization (NUM), providing insight on what they optimize and on the structures of network protocol stacks. In the form of 10 Questions and Answers, this paper presents a short survey of the recent efforts towards a systematic understanding of "layering" as "optimization decomposition". The overall communication network is modeled by a generalized NUM problem, each layer corresponds to a decomposed subproblem, and the interfaces among layers are quantified as functions of the optimization variables coordinating the subproblems. Furthermore, there are many alternative decompositions, each leading to a different layering architecture. Industry adoption of this unifying framework has also started. Here we summarize the current status of horizontal decomposition into distributed computation and vertical decomposition into functional modules such as congestion control, routing, scheduling, random access, power control, and coding. We also discuss under-explored future research directions in this area. More importantly than proposing any particular crosslayer design, this framework is working towards a mathematical foundation of network architectures and the design process of modularization

Scheduling for Optimal Rate Allocation in Ad Hoc Networks With Heterogeneous Delay Constraints

This paper studies the problem of scheduling in single-hop wireless networks with real-time traffic, where every packet arrival has an associated deadline and a minimum fraction of packets must be transmitted before the end of the deadline. Using optimization and stochastic network theory we propose a framework to model the quality of service (QoS) requirements under delay constraints. The model allows for fairly general arrival models with heterogeneous constraints. The framework results in an optimal scheduling algorithm which fairly allocates data rates to all flows while meeting long-term delay demands. We also prove that under a simplified scenario our solution translates into a greedy strategy that makes optimal decisions with low complexity

Optimal Power Control and Scheduling under Hard Deadline Constraints for Continuous Fading Channels

We consider a joint scheduling-and-power-allocation problem of a downlink cellular system. The system consists of two groups of users: real-time (RT) and non-real-time (NRT) users. Given an average power constraint on the base station, the problem is to find an algorithm that satisfies the RT hard deadline constraint and NRT queue stability constraint. We propose a sum-rate-maximizing algorithm that satisfies these constraints. We also show, through simulations, that the proposed algorithm has an average complexity that is close-to-linear in the number of RT users. The power allocation policy in the proposed algorithm has a closed-form expression for the two groups of users. However, interestingly, the power policy of the RT users differ in structure from that of the NRT users. We also show the superiority of the proposed algorithms over existing approaches using extensive simulations.Comment: Submitted to Asilomar 2017. arXiv admin note: text overlap with arXiv:1612.0832

Non-convex resource allocation in communication networks

The continuously growing number of applications competing for resources in current communication networks highlights the necessity for efficient resource allocation mechanisms to maximize user satisfaction. Optimization Theory can provide the necessary tools to develop such mechanisms that will allocate network resources optimally and fairly among users. However, the resource allocation problem in current networks has characteristics that turn the respective optimization problem into a non-convex one. First, current networks very often consist of a number of wireless links, whose capacity is not constant but follows Shannon capacity formula, which is a non-convex function. Second, the majority of the traffic in current networks is generated by multimedia applications, which are non-concave functions of rate. Third, current resource allocation methods follow the (bandwidth) proportional fairness policy, which when applied to networks shared by both concave and non-concave utilities leads to unfair resource allocations. These characteristics make current convex optimization frameworks inefficient in several aspects. This work aims to develop a non-convex optimization framework that will be able to allocate resources efficiently for non-convex resource allocation formulations. Towards this goal, a necessary and sufficient condition for the convergence of any primal-dual optimization algorithm to the optimal solution is proven. The wide applicability of this condition makes this a fundamental contribution for Optimization Theory in general. A number of optimization formulations are proposed, cases where this condition is not met are analysed and efficient alternative heuristics are provided to handle these cases. Furthermore, a novel multi-sigmoidal utility shape is proposed to model user satisfaction for multi-tiered multimedia applications more accurately. The advantages of such non-convex utilities and their effect in the optimization process are thoroughly examined. Alternative allocation policies are also investigated with respect to their ability to allocate resources fairly and deal with the non-convexity of the resource allocation problem. Specifically, the advantages of using Utility Proportional Fairness as an allocation policy are examined with respect to the development of distributed algorithms, their convergence to the optimal solution and their ability to adapt to the Quality of Service requirements of each application

Proportional Fair Coding for Wireless Mesh Networks

We consider multi–hop wireless networks carrying unicast flows for multiple users. Each flow has a specified delay deadline, and the lossy wireless links are modelled as binary symmetric channels (BSCs). Since transmission time, also called airtime, on the links is shared amongst flows, increasing the airtime for one flow comes at the cost of reducing the airtime available to other flows sharing the same link. We derive the joint allocation of flow airtimes and coding rates that achieves the proportionally fair throughput allocation. This utility optimisation problem is non–convex, and one of the technical contributions of this paper is to show that the proportional fair utility optimisation can nevertheless be decomposed into a sequence of convex optimisation problems. The solution to this sequence of convex problems is the unique solution to the original non–convex optimisation. Surprisingly, this solution can be written in an explicit form that yields considerable insight into the nature of the proportional fair joint airtime/coding rate allocation. To our knowledge, this is the first time that the utility fair joint allocation of airtime/coding rate has been analysed, and also, one of the first times that utility fairness with delay deadlines has been considered

Joint rate control and scheduling for providing bounded delay with high efficiency in multihop wireless networks

This thesis considers the problem of supporting traffic with elastic bandwidth requirements and hard end-to-end delay constraints in multi-hop wireless networks, with focus on source transmission rates and link data rates as the key resource allocation decisions. Specifically, the research objective is to develop a source rate control and scheduling strategy that guarantees bounded average end-to-end queueing delay and maximises the overall utility of all incoming traffic, using network utility maximisation framework. The network utility maximisation based approaches to support delay-sensitive traffic have been predominantly based on either reducing link utilisation, or approximation of links as M/D/1 queues. Both approaches lead to unpredictable transient behaviour of packet delays, and inefficient link utilisation under optimal resource allocation. On the contrary, in this thesis an approach is proposed where instead of hard delay constraints based on inaccurate M/D/1 delay estimates, traffic end-to-end delay requirements are guaranteed by proper forms of concave and increasing utility functions of their transmission rates. Specifically, an alternative formulation is presented where the delay constraint is omitted and sources’ utility functions are multiplied by a weight factor. The alternative optimisation problem is solved by a distributed scheduling algorithm incorporating a duality-based rate control algorithm at its inner layer, where optimal link prices correlate with their average queueing delays. The proposed approach is then realised by a scheduling algorithm that runs jointly with an integral controller whereby each source regulates the queueing delay on its paths at the desired level, using its utility weight coefficient as the control variable. Since the proposed algorithms are based on solving the alternative concave optimisation problem, they are simple, distributed and lead to maximal link utilisation. Hence, they avoid the limitations of the previous approaches. The proposed algorithms are shown, using both theoretical analysis and simulation, to achieve asymptotic regulation of end-to-end delay given the step size of the proposed integral controller is within a specified range

Joint Scheduling and Duty Cycle Control Framework for Hierarchical Machine-to-Machine Communication Networks.

PhDThis thesis presents a novel distributed optimisation framework for machine-tomachine (M2M) communication networks with dynamic traffic generation, heterogeneous applications and different device capabilities. The aim of the framework is to effectively manage the massive access of energy constrained M2M devices while satisfying different application requirements. The proposed framework has three control blocks which run at cluster heads and M2M gateways: i) The distributed duty cycle control that adapts to dynamic network traffics for IEEE 802.15.4 MAC layer protocol with stop-and-wait automatic repeat request (ARQ) and Go-Back-N ARQ schemes. ii) The cluster head control that applies dynamic programming (DP) and approximate dynamic programming (ADP) techniques to maximise single cluster utility while balancing the tradeoff between system performance and algorithm complexity. iii) The gateway control that applies network utility optimisation (NUM) and mixed integer programming (MIP) techniques to maximise the aggregated long-term network utility while satisfying different application requirements among clusters. Both theoretical and practical concerns are addressed by the proposed control framework. Simulation results show that the proposed framework effectively improve the overall network performance in terms of network throughput, energy efficiency, end-to-end delay and packet drop ratio.Chinese Scholarship Council (CSC)