Provision of multimedia services: the key to deployment of accessnetwork architectures in developing countries

Access networks have always been a very significant part of public network operator investments and operating costs. They have not, however, been a very dynamic part of telecom networks, planned, as they were, for the long term and usually with limited technological innovation. This is changing, and access networks are increasingly coming into focus for technological innovation and as platforms for provisioning new advanced services in a competitive business environment. New fiber, radio, and copper-based technologies, in combination with flexible multiplexers and management tools, provide new possibilities for improved quality of services, cost reduction, and provisioning of new advanced services. In order to fully benefit from these possibilities, to extend and upgrade existing as well as build completely new access networks, a flexible service-independent access network architecture and access network system are required. In this article a target access network architecture is suggested as well as an implementation scenario for developing countries     

Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing

The rapid growth of mobile internet services has yielded a variety of computation-intensive applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which enables mobile terminals to offload computation tasks to servers located at the edge of the cellular networks, has been considered as an efficient approach to relieve the heavy computational burdens and realize an efficient computation offloading. Driven by the consequent requirement for proper resource allocations for computation offloading via MEC, in this paper, we propose a Deep-Q Network (DQN) based task offloading and resource allocation algorithm for the MEC. Specifically, we consider a MEC system in which every mobile terminal has multiple tasks offloaded to the edge server and design a joint task offloading decision and bandwidth allocation optimization to minimize the overall offloading cost in terms of energy cost, computation cost, and delay cost. Although the proposed optimization problem is a mixed integer nonlinear programming in nature, we exploit an emerging DQN technique to solve it. Extensive numerical results show that our proposed DQN-based approach can achieve the near-optimal performance.     

Mobility management architectures based on joint mobile IP and SIP protocols

In the all-IP wireless networks beyond the third generation, mobility management can be effectively achieved by applying mobile IP (MIP) and the session initiation protocol (SIP) jointly. Nevertheless, an efficient combination of both protocols remains an open research issue. Conventional hybrid MIP-SIP mobility architectures operate MIP and SIP almost independently, resulting in significant redundant costs. This article investigates the representative hybrid MIP-SIP architectures and explores the joint optimizations between MIP and SIP for a more cost-efficient mobility support whilst utilizing their complementary power. Two novel design approaches are presented. The first approach culminates in a tightly integrated architecture, which merges the redundant mobility entities in MIP and SIP to yield maximum system efficiency. The other approach leads to a loosely integrated architecture, where necessary interactions are introduced between MIP and SIP mobility servers while their physical entities are kept intact. Major mobility procedures, including location update, session setup and handoff, are discussed in these architectures. The analytical results demonstrate that both proposed architectures outperform typical hybrid MIP-SIP architectures in terms of clear-cut reduced signaling costs     

On demand network-wide VPN deployment in GPRS

Mobile Internet requires enhanced security services available to all mobile subscribers in a dynamic fashion. A network-wide virtual private network deployment scenario over the General Packet Radio Service is proposed and analyzed from a security viewpoint. The proposed security scheme improves the level of protection that is currently supported in GPRS and facilitates the realization of mobile Internet. It secures data transmission over the entire network route from a mobile user to a remote server by utilizing the default GPRS ciphering over the radio interface, and by deploying an IP VPN over the GPRS core, as well as on the public Internet. Thus, on-demand VPN services are made available for all GPRS network subscribers and roaming users. The VPN functionality, which is based on the IPsec framework, is outsourced to the network infrastructure to eliminate the potential computational overhead on the mobile device. The VPN initialization and key agreement procedures are based on an Internet Key Exchange protocol proxy scheme, which enables the mobile station to initiate VPN establishment, while shifting the complex key negotiation to the network infrastructure. The deployed VPN operates transparently to the mobile subscribers' movement. The required enhancements for security service provision can be integrated in the existing network infrastructure; therefore, the propose security scheme can be employed as an add-on feature to the GPRS standard.     

移动边缘计算技术及其本地分流方案

移动边缘计算(mobile edge computing,MEC)技术通过为无线接入网提供IT和云计算能力,使得业务本地化、近距离部署成为可能,从而促使无线网络具备低时延、高带宽的传输能力,并且回传带宽需求的降低极大程度减少了运营成本.同时,MEC通过感知无线网络上下文信息(位置、网络负荷、无线资源利用率等)并向业务应用开放,可有效提升用户的业务体验,并且为创新型业务的研发部署提供平台.首先介绍MEC技术,细化并给出MEC平台框图.此外,针对基于MEC平台的本地分流功能,给出了详细的技术方案,并与3GPP本地分流方案LIPA/SIPTO进行对比分析.更进一步,针对MEC技术在网络应用中可能存在的问题与挑战进行了讨论,为后续研究发展提供参考.     

Precoding and channel state information sharing in cooperative macro base stations and femto sites

Femto cell technology is a promising solution for indoor coverage of cellular systems. The interference between macro and femto cells can be mitigated via cooperation between the macro base station (BS) and the inside femto sites (FSs). In this paper, the idea of multi‐cell multi‐input and multi‐output is introduced, whereby the macro BS shares the same frequency band with the inside FSs in support of the femto users. Both single‐user and multi‐user precoding at the macro BS are proposed to support the cooperative transmission between the macro BSs and FSs. In single‐user precoding and multi‐user precoding without power allocation, only the angle information of the FS‐user channels is required to be sent from the users to the macro BS. If the magnitude information is also sent by each user, multi‐user precoding with power allocation can be employed to support cooperation between macro BSs and FSs, which is an extension of the classical water‐filling optimization problem. Theoretical derivations and an iterative algorithm are both presented to solve this optimization problem. Analytical and simulation results with respect to the signal received with interferences validate the effectiveness of cooperation between the macros BSs and FSs.Copyright © 2012 John Wiley & Sons, Ltd.     

Data gathering and offloading in delay tolerant mobile networks

Mobile sensing emerges as an important application for mobile networks. Smartphones equipped with sensors are used to monitor a diverse range of human activities. One key and challenging procedure of the mobile sensing applications is data gathering, where the sensed data from distributed mobile nodes are captured and uploaded to the cloud or base station for further processing. Yet the mobile sensing application, which usually periodically generates some sensed data, would definitely deteriorate the 3G quality because the network cannot cope with the high demand; and users would be charged at high prices by using the 3G channel, which makes the mobile sensing application infeasible. In this paper, we proposed a hybrid data gathering and offloading algorithm DGO for the mobile sensing applications. Besides the direct uploading through 3G or Wifi offloading, the sensed data could also be forwarded to other peer nodes through short range communications. Nodes collect meta-data such as remaining energy, contact regularity, and expected contact duration to calculate the upload/offload utility and upload priority for data segments. Based on these utility factors, each data segment could decide its own approach at a specific time for uploading. Experimental studies show that DGO is efficient in data gathering and data offloading in mobile sensing applications. Given the low accessibility of Wifi APs, DGO still gains about more than 30 % of data offloading compared with existing algorithms without much extra transmission overhead or delay.     

Challenges and opportunities in immersive vehicular sensing: Lessons from urban deployments

Vehicles provide an ideal platforms for a plethora of emerging applications such as networked gaming, multimedia content delivery and urban sensing. Cars have no power constraints and they can be instrumented with high end computational units and graphic devices. The deployment at scale of urban vehicular systems, however, requires a careful design able to consider challenges across several domains. Vehicular systems are arguably a prominent example of cyber-physical systems. The development of such systems requires a truly multidisciplinary approach and a close integration between the application, communication, and physical domains. Hardware and software mounted on vehicles will face a harsh physical and communication environment that will greatly affect all the system components. In this paper we report on the challenges and opportunities for multimedia vehicular urban sensing systems based on our field experiences in Macao (China) and Los Angels (USA). We designed and built the components for a pollution monitoring system able to support closed-loop optimization between pollution and traffic management. Our initial set of prototype vehicles are now running in the city of Macao and they are measuring the air parameters as well as the urban traffic. The paper aims at exposing some of the issues encountered, outlining the problems of a city wide deployment, and augmenting our in-field experience with the results from large scale simulation studies.     

Secure and reliable computation offloading in blockchain-assisted cyber-physical IoT systems

With the development of the Cyber-Physical Internet of Things System (CPIoTS), the number of Cyber-Physical System (CPS) applications accessed in networks has increased dramatically. Latency-sensitive resource orchestration in CPS applications is extraordinarily essential for maintaining the Quality of Experience (QoE) for users. Although edge-cloud computing performs effectively in achieving latency-aware resource allocation in CPIoTS, existing methods fail to jointly consider the security and reliability requirements, thereby increasing the process latency of tasks and degrading the QoE of users. This paper aims to minimize the system latency of edge-cloud computing coupled with CPS while simultaneously considering the security and reliability requirements. We first consider a time-varying channel model as a Finite-State Markov Channel (FSMC) and propose a distributed blockchain-assisted CPIoTS to realize secure consensus and reliable resource orchestration by offloading computation tasks in edge-cloud computing. Moreover, we propose an efficient resource allocation algorithm, PPO-SRRA, that optimizes computing offloading and multi-dimension resource (e.g., communication, computation, and consensus resource) allocation by using a policy-based Deep Reinforcement Learning (DRL) method. The experimental results show that the proposed resource allocation scheme can reduce the system latency and ensure consensus security.     

基于NOMA的超密集MEC网络任务卸载和资源分配方案

为了提高移动边缘计算(mobile edge computing,MEC)网络的频谱效率,满足大量用户的服务需求,建立了基于非正交多址接入(non-orthogonal multiple access,NOMA)的超密集MEC系统模型。为了解决多个用户同时卸载带来的严重通信干扰等问题,以高效利用边缘服务器资源,提出了一种联合任务卸载和资源分配的优化方案,在满足用户服务质量的前提下最小化系统总能耗。该方案联合考虑了卸载决策、功率控制、计算资源和子信道资源分配。仿真结果表明,与其他卸载方案相比,所提方案可以在满足用户服务质量的前提下有效降低系统能耗。     

On the optimal random deployment of wireless sensor networks in non-homogeneous scenarios

Random scattering of WSNs is needed in many practical cases due to the large scale of the network required or to the inaccessibility of the terrain. However several important features of deployments of this type have been neglected due to their analytical complexity. Node placement must guarantee correct operation: if nodes are too separated many would be isolated and data would not reach the sinks. Besides, if the nodes are too close, the area covered would be small and little information would be retrieved. Moreover, the target area cannot be considered homogeneous since in real-life situations some zones are more important than others. This paper addresses these constraints by proposing and solving an optimization problem which maximizes network sensing coverage. In our model several clusters of nodes are spread over the target area following Gaussian random distributions, and the goal is to decide the optimal launch point and the dispersion for each cluster. This corresponds to real situations where clusters are dropped in an airborne launch in which dispersion is controlled by the release altitude. The problem is solved by considering iterative steps where single cluster deployments are addressed. Several tests validate our approach and indicate that our method outperforms previous approaches, especially in deployments with a low number of nodes, which are more challenging from the optimization perspective.     

异构蜂窝网络中分层任务卸载：建模与优化

为提高计算任务卸载的效率,提出了一种基于D2D通信、移动边缘计算和云计算的分层任务卸载框架,并引入D2D协作中继技术辅助用户接入远端计算资源。针对所提任务卸载框架在多用户场景中可能存在上行通信拥塞、边缘计算资源受限、D2D复用干扰和云计算回程时延等问题,设计了一种基于博弈论的卸载调度和负载均衡方案,充分利用了所提任务卸载框架中各层计算和通信资源。仿真结果表明,所提方案能够有效降低端到端时延和卸载能耗,并在资源受限的条件下具有良好的稳定性。     

Uplink user capacity in a CDMA macrocell with a hotspot microcell: exact and approximate analyses

This paper studies the number of voice users (user capacity) supported on the uplink of a single-macrocell/single-microcell code-division multiple-access system. A "hotspot" microcell is embedded within a larger macrocell and operates over the same bandwidth as the larger cell. Analytic methods are presented for computing user capacity which account for propagation loss, multiple-access interference, power control, and random locations of user terminals, as well as two distinct methods by which users select base stations (tiers). Along with the exact user capacity, a technique for making accurate approximations is also presented. Simulation results verify both the exact and approximate analytical methods. This simulation is also employed to study the capacity gains of a third, more optimal, tier-selection scheme. These results point to differences in capacity performance based on the tier-selection method, as well as on the traffic density within the hotspot region.     

On joint coding for watermarking and encryption

In continuation of earlier work, where the problem of joint information embedding and lossless compression (of the composite signal) was studied in the absence and in the presence of attacks, here we consider the additional ingredient of protecting the secrecy of the watermark against an unauthorized party, which has no access to a secret key shared by the legitimate parties. In other words, we study the problem of joint coding for three objectives: information embedding, compression, and encryption. Our main result is a coding theorem that provides a single-letter characterization of the best achievable tradeoffs among the following parameters: the distortion between the composite signal and the covertext, the distortion in reconstructing the watermark by the legitimate receiver, the compressibility of the composite signal (with and without the key), and the equivocation of the watermark, as well as its reconstructed version, given the composite signal. In the attack-free case, if the key is independent of the covertext, this coding theorem gives rise to a threefold separation principle that tells that asymptotically, for long block codes, no optimality is lost by first applying a rate-distortion code to the watermark source, then encrypting the compressed codeword, and finally, embedding it into the covertext using a previously proposed embedding scheme. In the more general case, however, this separation principle is no longer valid, as the key plays an additional role of side information used by the embedding unit     

On the benefits of multi-path recovery in flexgrid optical networks

We propose a new recovery scheme, called multi-path recovery (MPR), specifically designed for flexgrid-based optical networks. It combines protection and restoration schemes to jointly recover, in part or totally, the bitrate requested by client demands in case of failure. We define the bitrate squeezed recovery optimization (BRASERO) problem to maximize the amount of bitrate which is recovered in case of failure of any single fiber link; a mixed integer linear programming formulation for the BRASERO problem is provided. However, since their exact solutions become impractical when real-sized network and traffic instances are considered, we develop a heuristic algorithm which provides a much better trade-off between optimality and complexity. Exhaustive numerical experiments carried out over realistic network topologies and traffic scenarios show that the efficiency of the proposed MPR scheme approaches that of restoration while providing recovery times as short as protection schemes.     

On the design of node architectures and MAC protocols for optical burst-switched ring networks

Efficient multiple-token-based MAC protocols have been proposed for optical burst-switched (OBS) unidirectional ring networks using a TT-TR-based node architecture in our previous research. However, the unidirectional OBS ring network is difficult to scale to larger networks. As wavelengths accessibilities are dominated by tokens, network performance is restricted by the frequency of capturing a token. If the network is too large, it takes a long time for tokens to rotate. Thus, a destination queue may wait for a long time to be served, which results in large queuing delays and inefficiency of network resource utilization. In order to improve network efficiency and scalability for OBS ring networks using multiple tokens, this work is extended to a bidirectional ring system that uses the tunable transmitter and tunable receiver (TT-TR)-based node architecture with two pairs of transceivers, so that each queue can be served by tokens from both directions. Furthermore, two kinds of node architectures differing in sharing the two pairs of transceivers, either shared or not, are proposed. Then, two MAC protocols considering different queue scheduling algorithms are proposed for the ring network using the proposed node architectures, in order to use the network resources more efficiently. They are improved from general round-robin (GRR) and termed as half-ring round-robin (HfRR) and co-work round-robin (CoRR), respectively. The network performance of the two proposed node architectures and the two proposed MAC protocols for the networks using them as well as the network scalability are evaluated with the OPNET simulator.     

Speed and area tradeoffs in cluster-based FPGA architectures

One way to reduce the delay and area of field-programmable gate arrays (FPGAs) is to employ logic-cluster-based architectures, where a logic cluster is a group of logic elements connected with high-speed local interconnections. In this paper, we empirically evaluate FPGA architectures with logic clusters ranging in size from 1 to 20, and show that compared to architectures with size 1 clusters, architectures with size 8 clusters have 23% less delay (30% faster clock speed) and require 14% less area. We also show that FPGA architectures with large cluster sizes can significantly reduce design compile time-an increasingly important concern as the logic capacity of FPGA's rises. For example, an architecture that uses size 20 clusters requires seven times less compile time than an architecture with size 1 clusters     

Future directions in packet radio architectures and protocols

The technology of packet switching over multihop, multiple-access channels has evolved to the point at which its protocols can now support internetwork operation of medium-size networks whose nodes possess some degree of mobility. As regards the needs and challenges of the future operating environment, it is clear that these can be met only by enhancing the packet radio architecture and its protocols. We discuss several enhancements that allow the organization of large, dynamic networks that can operate over multiple channels, adapt to varying conditions, and possess self-monitoring and self-control capabilities. As these areas are examined, the attendant issues and tradeoffs are discussed; in addition, some protocols and information regarding their performance are presented.     

On the benefits of location-based relay selection in mobile wireless networks

We consider infrastructure-based mobile networks that are assisted by a single relay transmission where both the downstream destination and relay nodes are mobile. Selecting the optimal transmission path for a destination node requires up-to-date link quality estimates of all relevant links. If the relay selection is based on link quality measurements, the number of links to update grows quadratically with the number of nodes, and measurements need to be updated frequently when nodes are mobile. In this paper, we consider a location-based relay selection scheme where link qualities are estimated from node positions; in the scenario of a node-based location system such as GPS, the location-based approach reduces signaling overhead, which in this case only grows linearly with the number of nodes. This paper studies these two relay selection approaches and investigates how they are affected with varying information update interval, node mobility, location inaccuracy, and inaccurate propagation model parameters. Our results show that location-based relay selection performs better than SNR-based relay selection at typical levels of location error when medium-scale fading can be neglected or accurately predicted.