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Mobile edge computing is popular for providing services with low latency and high privacy. It becomes more powerful by leveraging the widely deployed Small cell Base Stations (SBS) with zooming cells for energy-efficient service placement. However, the literature ignores the joint optimization of SBS power control and service placement. The Quality of Services (QoS) guarantee is also challenging, taking into account the component dependency and parallelization in multi-component services and the resource slicing for separated service deployment. Moreover, prior works assume the same amount of allocated resources of links on a placed path for service edge allocation, leading to the ossification of resource allocation and inevitable resource fragments. Towards the above challenges, this paper addresses the energy-efficient and flexible service placement in cell zooming enabled Mobile Edge Cloud (MEC) networks. The delay of multi-component services is constructed depending on the allocated resource slice. Besides, the joint optimization of service placement and SBS power control is formulated and transformed into a Mixed Integer Linear Programming (MILP). More importantly, the equivalent bandwidth for an edge allocation is defined and analyzed to obtain flexible edge placement with minimum resource cost. Leveraging the results of MILP, an Energy-efficient Service placement algorithm based on equivalent Bandwidth in Cell zooming enabled MEC networks (ESBC) is proposed to improve the probability of successful service placement with QoS guarantee by optimizing the delay distribution among components and edges and reducing resource fragments. Finally, simulation results validate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Orthogonal Frequency Division Multiple Access (OFDMA) is an attracting system for combating the frequency selective fading. It's widely considered as a promising candidate modulation and access scheme for next generation mobile communication systems. However, the explosive growth of multimedia applications raises higher performance requirements for Radio Resource Management (RRM) in OFDMA system. In particular, limited bandwidth and fierce resource competition impose a challenging issue on the design of packet scheduler. In this paper, we propose two scheduling algorithms applicable to mixed services (i.e., real-time and non-real-time services), that is QoS-oriented Dynamic Threshold Control (DTC) algorithm and fairness-oriented Fairness Aware and QoS Aware (FAQA) algorithm. These two algorithms are both composed of two stages, i.e., initial subcarrier allocation and subcarrier reallocation. For the DTC algorithm, in the stage of initial subcarrier allocation, based on the different metrics to weigh QoS between both services, we design a unique scheduling strategy for each type of service. A dynamic threshold is adopted to help users quickly recover from starvation, so that any one user in system can escape from severely degraded QoS. In the stage of subcarrier reallocation, we will reallocate the surplus subcarriers from the buffer-empty users to the buffer-nonempty users so as to increase spectrum efficiency. For FAQA algorithm, in the stage of initial subcarrier allocation, for the purpose of achieving Proportional Fairness (PF) with lower complexity, we deduce a simple scheduling strategy satisfying PF criterion by means of Greedy algorithm. In the stage of subcarrier reallocation, in order to increase the number of users satisfying QoS requirements, we'll reallocate the surplus subcarriers from the QoS-satisfied users to the QoS-unsatisfied users. Simulation results demonstrate that, on one hand, the DTC algorithm not only guarantees the quality of both services, but also increases the spectrum efficiency; on the other hand, the FAQA algorithm well maintains the fairness among users, and increases the QoS satisfaction degree at the same time. [ABSTRACT FROM AUTHOR]

The emerging 5G applications and the connectivity of billions of devices have driven the investigation of multi-domain heterogeneous converged optical networks. To support emerging applications with their diverse quality of service requirements, network slicing has been proposed as a promising technology. Network virtualization is an enabler for network slicing, where the physical network can be partitioned into different configurable slices in the multi-domain heterogeneous converged optical networks. An efficient resource allocation mechanism for multiple virtual networks in network virtualization is one of the main challenges referred as virtual network embedding (VNE). This paper is a survey on the state-of-the-art works for the VNE problem towards multi-domain heterogeneous converged optical networks, providing the discussion on future research issues and challenges. In this paper, we describe VNE in multi-domain heterogeneous converged optical networks with enabling network orchestration technologies and analyze the literature about VNE algorithms with various network considerations for each network domain. The basic VNE problem with various motivations and performance metrics for general scenarios is discussed. A VNE algorithm taxonomy is presented and discussed by classifying the major VNE algorithms into three categories according to existing literature. We analyze and compare the attributes of algorithms such as node and link embedding methods, objectives, and network architecture, which can give a selection or baseline for future work of VNE. Finally, we explore some broader perspectives in future research issues and challenges on 5G scenario, field trail deployment, and machine learning-based algorithms. [ABSTRACT FROM AUTHOR]

Highlights: [•] Our work has considered the QoS factors and constructed a reward function to model the QoS properties. [•] Our work has considered MT’s velocity, network access cost and switching cost for vertical handoff decision. [•] We have applied G1 and entropy methods to calculate the weight of each QoS factor in the reward function. [•] By taking the MT’s velocity into consideration, our work can avoid unnecessary handoffs. [ABSTRACT FROM AUTHOR]

Abstract: Saving the electrical requirements of network operators around the world makes power costs show a continuously decreasing trend. However, reducing the power costs is not only one way of gaining the marginal profit, a network operator also needs providing high-level quality of service (QoS), as well as employs effective strategies of pricing and hybrid grooming (i.e., integration of traffic grooming with an optical bypass) to make more users wish to pay the expense for their applications. In the final, users enjoy their services meanwhile operators obtain high profit in a power-efficient way, i.e., “double-win”. Accordingly, we propose the fast sub-optimal heuristics including Single-hop and Power-efficient Grooming algorithm based on Game theory (SPG2) as well as Multi-hop and Power-efficient Grooming algorithm based on Game theory (MPG2). Simulation results demonstrate that, compared with SPG2, MPG2 has the better comprehensive performance of both power efficiency and double-win between user and network operator in IP over WDM networks. [Copyright &y& Elsevier]

Abstract: With the network size increasing, the optical backbone is divided into multiple domains and each domain has its own network operator and management policy. At the same time, the failures in optical network may lead to a huge data loss since each wavelength carries a lot of traffic. Therefore, the survivability in multi-domain optical network is very important. However, existing survivable algorithms can achieve only the unilateral optimization for profit of either users or network operators. Then, they cannot well find the double-win optimal solution with considering economic factors for both users and network operators. Thus, in this paper we develop the multi-domain network model with involving multiple Quality of Service (QoS) parameters. After presenting the link evaluation approach based on fuzzy mathematics, we propose the game model to find the optimal solution to maximize the user’s utility, the network operator’s utility, and the joint utility of user and network operator. Since the problem of finding double-win optimal solution is NP-complete, we propose two new hybrid protection algorithms, Intra-domain Sub-path Protection (ISP) algorithm and Inter-domain End-to-end Protection (IEP) algorithm. In ISP and IEP, the hybrid protection means that the intelligent algorithm based on Bacterial Colony Optimization (BCO) and the heuristic algorithm are used to solve the survivability in intra-domain routing and inter-domain routing, respectively. Simulation results show that ISP and IEP have the similar comprehensive utility. In addition, ISP has better resource utilization efficiency, lower blocking probability, and higher network operator’s utility, while IEP has better user’s utility. [Copyright &y& Elsevier]