CDNPatch: a cost‐effective failover mechanism for hybrid CDN‐P2P live streaming systems

Among the most well‐established live media distribution technologies is content delivery network (CDN), which improves user‐perceived quality of service by delivering content from proxy servers deployed at the Internet's edge. In recent years, CDN providers started to tap into their subscribers' peer‐to‐peer (P2P) capacity to alleviate their server costs. Under the inherent peer dynamics, a major challenge of these hybrid CDN‐P2P systems is to provide efficient failure recovery with good quality of service guarantees at a reduced server cost. In this work we propose a cost‐effective failover solution named CDNPatch to address the aforementioned problem. CDNPatch enables peers to periodically precompute a few backup content suppliers by efficient information exchange and maintenance algorithms, and leverages auxiliary CDN servers and an economic server provisioning algorithm to reduce the chance of playback interruption occurring to peers. Our simulation results show that CDNPatch can mask the impact of peer dynamics of 3 real P2P systems, namely, SOPCast, PPStream, and PPTV, with 100 % failure recovery success rate and a failure recovery time less than 1 second at a cost of small P2P communication overhead of less than 1 kilobits per second, while using only 10%, 21%, and 51%, respectively, of the pure CDN scheme's server consumption.     

基于拍卖的P2P内容分发网络带宽分配机制

为了解决P2P内容分发网络中带宽资源稀缺且分配不合理这一突出问题,抑制节点的自私性行为,设计了一种基于拍卖的带宽分配机制。该机制通过上载带宽支付方式,迫使自私请求节点选择合适的带宽需求,使得整个P2P网络中的节点良性竞争带宽资源,避免了"公共地悲剧"的发生;且带宽分配算法在资源节点和请求节点并行执行,能很好适应P2P网络的分布式特性。仿真结果表明,该机制能够有效遏制搭便车行为,从而缩短P2P内容分发的平均完成时间,降低内容源服务器的上传数据比例。     

Modelling and analysis of routing and resource allocation techniques in multi‐service networks

In this paper a novel call level model based on the extension of the classical Erlang multi‐rate model for broadband integrated services networks is proposed. We use the model to study routing strategies in multi‐service networks where service classes with/without QoS guarantees coexist. Examples for such networks include ATM and IP‐based integrated networks. In ATM, the CBR and VBR service classes provide QoS guarantees, while the ABR and UBR service classes are of the best effort type. In IP, traditional TCP/IP traffic is of the best effort type, while new protocols like the RSVP or the differentiated services with central resource handling attempt to support QoS parameters. The coexistence of guaranteed and best effort traffic gives rise to new challenging problems since for a given elastic (best effort) connection the bottleneck link determines the available bandwidth and thereby puts constraints on the bandwidth at the other links along the connection's path. Since the available bandwidth fluctuates in time following the load on the links, routing and link allocation in this environment together with blocking probability calculations and fairness issues need to be studied. By means of our proposed model we are able to conduct a survey of various routing and link allocation techniques as well as to develop a modified shortest path routing algorithm which, according to the numerical examples, performs well in this environment. Copyright © 1999 John Wiley & Sons, Ltd.     

Joint resource allocation for hybrid NOMA-assisted MEC in 6G networks

Multi-access Edge Computing (MEC) is an essential technology for expanding computing power of mobile devices, which can combine the Non-Orthogonal Multiple Access (NOMA) in the power domain to multiplex signals to improve spectral efficiency. We study the integration of the MEC with the NOMA to improve the computation service for the Beyond Fifth-Generation (B5G) and the Sixth-Generation (6G) wireless networks. This paper aims to minimize the energy consumption of a hybrid NOMA-assisted MEC system. In a hybrid NOMA system, a user can offload its task during a time slot shared with another user by the NOMA, and then upload the remaining data during an exclusive time duration served by Orthogonal Multiple Access (OMA). The original energy minimization problem is non-convex. To efficiently solve it, we first assume that the user grouping is given, and focuses on the one group case. Then, a multilevel programming method is proposed to solve the non-convex problem by decomposing it into three subproblems, i.e., power allocation, time slot scheduling, and offloading task assignment, which are solved optimally by carefully studying their convexity and monotonicity. The derived solution is optimal to the original problem by substituting the closed expressions obtained from those decomposed subproblems. Furthermore, we investigate the multi-user case, in which a close-to-optimal algorithm with low-complexity is proposed to form users into different groups with unique time slots. The simulation results verify the superior performance of the proposed scheme compared with some benchmarks, such as OMA and pure NOMA.     

An efficient cooperative hybrid routing protocol for hybrid wireless mesh networks

Hybrid wireless mesh networks are the most generic types of wireless mesh networks. Unlike static mesh routers, which have multiple radio interfaces and almost no energy constraint, mobile mesh clients are usually equipped with a single radio interface and have energy limitations. A cooperative hybrid routing protocol (CHRP) combining advantages of proactive and reactive routing protocols by letting them work cooperatively is proposed in this paper, which can adapt to features of both routers and clients. In CHRP, in order to make a proper route selection, channel condition, interference and constrained energy of clients are considered in the node-aware routing metric. Besides, a cross-layer approach is used in CHRP. Both gateway and client oriented data flows are considered comprehensively. The simulation results using ns-3 show the advantage of the proposed CHRP in terms of average packet loss rate, average latency, average network throughput, average energy consumption of clients and the minimum residual energy of clients.     

Joint resource allocation,routing and CAC for uplink OFDMA networks with cooperative relaying

In this paper, we propose a joint resource allocation, routing, and connection admission control (CAC) scheme for uplink transmission in orthogonal frequency division multiple access (OFDMA) relay networks with cooperative relaying. For cooperative relaying, relay station can relay uplink data from mobile station (MS) to base station with cooperation of the MS using transmit diversity. Transmit diversity can be achieved by virtual MISO via distributed space–time coding. The proposed scheme jointly allocates OFDMA resources and selects path for each user with CAC to maximize the upink throughput of cooperative OFDMA relay networks. The basic OFDMA resource unit is considered as a resource element which is one subcarrier over one OFDMA symbol. An efficient multi-choice multi-dimensional knapsack (MMKP) algorithm is presented for the proposed scheme. The proposed MMKP algorithm provides a unified framework which is applicable to OFDMA networks with and without cooperative relaying. We evaluate the performance of the proposed scheme with and without cooperative relaying in a hilly terrain with heavy tree density by using OPNET-based simulation. We show that the cooperative relaying improve the uplink system throughput compared with non-cooperative relaying, and the proposed scheme outperforms the conventional link quality-based scheme in both cooperative and non-cooperative relay networks.     

Resource planning and bandwidth allocation in hybrid fiber–coax residential networks

The introduction of new high bandwidth services such as video-on-demand by cable operators will put a strain on existing resources. It is important for cable operators to know how many resources to commit to the network to satisfy customer demands. In this paper, we develop models of voice and video traffic to determine the effect of demand growth on hybrid fiber–coax networks. We obtain a set of guidelines that network operators can use to build out their networks in response to increased demand. We begin with one type of traffic and generalize to an arbitrary number of high-bandwidth constant bit rate (CBR) like services to obtain service blocking probabilities. We consider the effect of supporting variable bit rate (VBR) packet-switched traffic in addition to CBR services. These computations help us to determine how cable networks would function under various conditions (i.e., low, medium, and heavy loads). We also consider how the growth rate of the popularity of such services would change over time, and how this impacts network planning. Our findings will help cable operators estimate how much bandwidth they need to provision for a given traffic growth model and connection blocking requirement.     

一种基于能耗均衡的ZigBee网络高效混合路由算法

针对目前ZigBee网络混合路由算法寻找开销偏大、能耗不均的问题,提出一种高效混合路由算法( EHCA)。通过采用跨层泛听与优先使用深度大、剩余能量多的节点进行路由的方式,减少部分泛洪寻路分组的转发,均衡节点能耗。仿真结果表明,EHCA的节点能耗均衡、路由开销和网络寿命等性能均优于混合路由算法和树路由算法。     

An uplink resource allocation scheme for OFDMA‐based cognitive radio networks

Cognitive radio makes it possible for an unlicensed user to access a spectrum unoccupied by licensed users. In cognitive radio networks, extra constraints on interference temperature need to be introduced into radio resource allocation. In this paper, the uplink radio resource allocation is investigated for OFDMA‐based cognitive radio networks. In consideration of the characteristics of cognitive radio and OFDMA, an improved water‐filling power allocation scheme is proposed under the interference temperature constraints for optimal performance. Based on the improved water‐filling power allocation, a simple subcarrier allocation algorithm for uplink is proposed. The subcarrier allocation rules are obtained by theoretical deduction. In the uplink subcarrier allocation algorithm, the subcarriers are allocated to the users with the best channel quality initially and then adjusted to improve the system performance. A cursory water‐filling level estimation method is used to decrease the complexity of the algorithm. Asymptotic performance analysis gives a lower bound of the stability of the water‐filling level estimation. The complexity and performance of the proposed radio resource allocation scheme are investigated by theoretical analysis and numerical results. Copyright © 2008 John Wiley & Sons, Ltd.     

Dynamic resource allocation for DVB‐RCS networks

To provide high‐speed multimedia services using the digital video broadcasting‐return channel satellite (DVB‐RCS) standard, it is imperative to efficiently assign timeslots according to user demands and dynamically take into account the variations of the propagation conditions. In satellite networks operating above 10 GHz, rain fading constitutes the dominant factor deteriorating the quality of service. In this paper, a novel two‐phase resource allocation scheme for a DVB‐RCS compliant satellite network is proposed. The scheme operates in two phases, the resource calculation and the resource assignment. In the resource calculation phase, based on a dynamic channel model, an efficient algorithm is presented to determine the superframe design that maximizes system throughput. In the resource assignment phase, a novel Hybrid Bin‐packing algorithm is introduced maximizing the utilization of the multi‐frequency time division multiple access frame. The proposed algorithm has been compared with existing schemes exhibiting significantly better results with regard to overall system throughput. Copyright © 2008 John Wiley & Sons, Ltd.     

DCLRRA: Distributed cross‐layer routing and resource allocation techniques for OFDMA‐based broadband wireless networks

In this study, we develop a fully distributed routing protocol for OFDMA‐based multihop broadband wireless access (BWA) networks such as those of IEEE 802.16j. We refer to this protocol as the DCLRRA protocol. DCLRRA is based on autonomous resource allocation schemes that we also derive in this paper. The routing protocol's selection of the proper resource allocation scheme is based on whether the relay stations (RSs) are nomadic or stationary. While we develop the autonomous resource allocation schemes, we exploit the multi‐user capabilities of the OFDMA physical layer. This allows simultaneous data transmission sessions within the same neighborhood while offering a total elimination of interference between transmitting nodes. The direct result of this strategy is increased throughput with high utilization of the communication channel. We examine our routing technique to show its performance merits through extensive simulations. Copyright © 2010 John Wiley & Sons, Ltd.     

An SDN‐based scalable routing and resource management model for service provider networks

Volume of the Internet traffic has increased significantly in recent years. Service providers (SPs) are now striving to make resource management and considering dynamically changing large volume of network traffic. In this context, software defined networking (SDN) has been alluring the attention of SPs, as it provides virtualization, programmability, ease of management, and so on. Yet severe scalability issues are one of the key challenges of the SDN due to its centralized architecture. First of all, SDN controller may become the bottleneck as the number of flows and switches increase. It is because routing and admission control decisions are made per flow basis by the controller. Second, there is a signaling overhead between the controller and switches since the controller makes decisions on behalf of them. In line with the aforementioned explanations, this paper proposes an SDN‐based scalable routing and resource management model (SRRM) for SPs. The proposed model is twofold. SRRM performs routing, admission control, and signaling operations (RASOs) in a scalable manner. Additionally, resource management has also been accomplished to increase link use. To achieve high degree of scalability and resource use, pre‐established paths (PEPs) between each edge node in the domain are provided. The proposed controller performs RASOs based on PEPs. The controller also balances the load of PEPs and adjusts their path capacities dynamically to increase resource use. Experimental results show that SRRM can successfully perform RASOs in a scalable way and also increase link use even under heavy traffic loads.     

Energy‐efficient resource allocation for lifetime maximization in M2M networks

Machine‐to‐machine (M2M) communications is one of the major enabling technologies for the realization of the Internet of Things (IoT). Most machine‐type communication devices (MTCDs) are battery powered, and the battery lifetime of these devices significantly affects the overall performance of the network and the quality of service (QoS) of the M2M applications. This paper proposes a lifetime‐aware resource allocation algorithm as a convex optimization problem for M2M communications in the uplink of a single carrier frequency division multiple access (SC‐FDMA)‐based heterogeneous network. A K‐means clustering is introduced to reduce energy consumption in the network and mitigate interference from MTCDs in neighbouring clusters. The maximum number of clusters is determined using the elbow method. The lifetime maximization problem is formulated as a joint power and resource block maximization problem, which is then solved using Lagrangian dual method. Finally, numerical simulations in MATLAB are performed to evaluate the performance of the proposed algorithm, and the results are compared to existing heuristic algorithm and inbuilt MATLAB optimal algorithm. The simulation results show that the proposed algorithm outperforms the heuristic algorithm and closely model the optimal algorithm with an acceptable level of complexity. The proposed algorithm offers significant improvements in the energy efficiency and network lifetime, as well as a faster convergence and lower computational complexity.     

An efficient and generic downlink resource allocation procedure for pre‐5G networks

This paper addresses the downlink resource allocation problem in pre‐5G (LTE‐B) networks. At each time slot, the problem is to share the radio resources between users in order to maximize a given objective function. We expressed this problem considering the LTE standard constraints, which are rarely considered in the literature. Mainly, for any given user, the base station is constrained to transmit with a single modulation and coding scheme. We show that this problem is non‐deterministic polynomial‐time hard, and therefore, we propose a generic approximation algorithm that covers a large variety of objectives. This algorithm is composed of three routines that enable an effective resource sharing procedure. The first routine computes a solution for a relaxation of our main problem, while the second routine selects the most suitable modulation and coding scheme for each user. Finally, the last routine effectively distributes the unallocated resources. For the max rate policy, simulation results show that our algorithm outperforms other existing algorithms in terms of capacity and remains close to the optimal. Under the proportional fairness policy, our solution also provides a very good fairness while maintaining a near‐optimal capacity. Copyright © 2016 John Wiley & Sons, Ltd.     

Energy‐efficient resource allocation in D2D communications for energy harvesting–enabled NOMA‐based cellular networks

In this paper, we propose an energy‐efficient power control and harvesting time scheduling scheme for resource allocation of the subchannels in a nonorthogonal multiple access (NOMA)–based device‐to‐device (D2D) communications in cellular networks. In these networks, D2D users can communicate by sharing the radio resources assigned to cellular users (CUs). Device‐to‐device users harvest energy from the base station (BS) in the downlink and transmit information to their receivers. Using NOMA, more than one user can access the same frequency‐time resource simultaneously, and the signals of the multiusers can be separated successfully using successive interference cancellation (SIC). In fact, NOMA, unlike orthogonal multiple access (OMA) methods, allows sharing the same frequency resources at the same time by implementing adaptive power allocation. Our aim is to maximize the energy efficiency of the D2D pairs, which is the ratio of the achievable throughput of the D2D pairs to their energy consumption by allocating the proper subchannel of each cell to each device user equipment (DUE), managing their transmission power, and setting the harvesting and transmission time. The constraints of the problem are the quality of service of the CUs, minimum required throughput of the subchannels, and energy harvesting of DUEs. We formulate the problem and propose a low‐complexity iterative algorithm on the basis of the convex optimization method and Karush‐Kuhn‐Tucker conditions to obtain the optimal solution of the problem. Simulation results validate the performance of our proposed algorithm for different values of the system parameters.     

An autonomic risk‐ and penalty‐aware resource allocation with probabilistic resource scaling mechanism for multilayer cloud resource provisioning

Cloud computing environment allows presenting different services on the Internet in exchange for cost payment. Cloud providers can minimize their operational costs by auto‐scaling of the computational resources based on demand received from users. However, the time and cost required to increase and decrease the number of active computational resources are among the biggest limitations of scalability. Thus, auto‐scaling is considered as one of the most important challenges in the field of cloud computing. The present study aimed to present a new solution to automatic scalability of resources for multilayered cloud applications under the Monitor‐Analysis‐Plan‐Execute‐Knowledge loop. In addition, the Google penalty payment model was used to model the penalty costs in the problem and to accurately evaluate the earned profit. A hybrid resource load prediction algorithm was proposed to evaluate the future of resources in each cloud layer. Further, we used statistical solution to determine the statuses of VMs in addition to presenting a risk‐aware algorithm to allocate the user requests to active resources. The experimental results by Cloudsim indicated the improvement of the proposed approach in terms of operational costs, the number of used resources, and the amount of profit.     

Dynamic power allocation and routing for time-varying wireless networks

We consider dynamic routing and power allocation for a wireless network with time-varying channels. The network consists of power constrained nodes that transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (/spl lambda//sub ij/) that the system can stably support-where /spl lambda//sub ij/ represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed that stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an ad hoc wireless network, where channel variations are due to user mobility. Centralized and decentralized implementations are compared, and the stability region of the decentralized algorithm is shown to contain that of the mobile relay strategy developed by Grossglauser and Tse (2002).     

Frequency resource allocation strategy with QoS support in hybrid cellular and Device‐to‐Device networks

Hybrid networks, comprising a conventional cellular network overlaid with Device‐to‐Device (D2D), offer efficient way to improve system throughput. In this paper, a novel orthogonal frequency‐division multiple access channel‐assignment method is proposed for hybrid network. The proposed approach is optimal in terms of throughput and is subjected to a sensible QoS requirement, which guarantees that macrocell and D2D achieve a prescribed data rate and outage probability, respectively. Our solution consists of two phases. In the first phase, the minimum sub‐channels are allocated to the macrocell to satisfy their data rate requirements. This problem is mapped to the 0‐1 Knapsack Problem and solved by integer programming based Lagrange dual approach. In the second phase, the redundant sub‐channels are allocated to D2D pairs to maximize the throughput of D2D networks. An interference management scheme is proposed to guarantee the outage probability of D2D communications. A cluster is taken as the unit for frequency reuse among D2D pairs. The problem of clustering is mapped to the MAX k‐CUT problem in graph theory and is solved by graph‐based heuristic algorithm. Extensive simulations demonstrate the superior performance of the proposed solution compared with the existing scheme. Copyright © 2014 John Wiley & Sons, Ltd.