Energy and Latency-Aware Scheduling Under Channel Uncertainties in LTE Networks for Massive IoT

The machine-to-machine (M2M) communication is an enabler technology for internet of things (IoT) that provides communication between machines and devices without human intervention. One of the main challenges in IoT is managing a large number of machine-type communications co-existing with the human to human (H2H) or human type communications. Long term evolution (LTE) and LTE-advanced (LTE-A) technologies due to their inherent characteristics like high capacity and flexibility in data access management are appropriate choices for M2M/IoT systems. In this paper, a two-phase intelligent scheduling mechanism based on interval type-2 fuzzy logic to (1) satisfy QoS requirements, (2) ensure fair resource allocation and (3) control energy level of devices for coexistence of M2M/H2H traffics in LTE-A networks, is presented. The proposed interval type-2 fuzzy Logic mechanism enhances data traffic efficiency by predicting and handling the network uncertainties. The performance of the proposed algorithm is evaluated in terms of various metrics such as delay, throughput, and bandwidth utilization.     

5G异构网络中基于优先级的深度强化学习联合资源分配

为了研究基于深度强化学习(Deep Reinforcement Learning, DRL)的5G异构网络模型的性能,同时在最小化系统能耗并满足不同类型终端用户的服务质量要求的基础上制定合理的资源分配方案,提出了一种基于DRL的近端策略优化算法,并结合一种基于优先级的分配策略,引入了海量机器类型通信、增强移动宽带和超可靠低延迟通信业务。所提算法相较于Greedy和DQN算法,网络延迟分别降低73.19%和47.05%,能耗分别降低9.55%和6.93%,而且可以保证能源消耗和用户延迟之间的良好权衡。     

An efficient resource allocation to improve QoS of 5G slicing networks using general processor sharing‐based scheduling algorithm

Fifth generation (5G) slicing is an emerging technology for software‐defined networking/network function virtualization–enabled mobile networks. Improving the utilization and throughput to meet the quality of service (QoS) requirements of 5G slicing is very important for the operators of mobile networks. With growing data traffic from different applications of numerous smart mobile devices having several QoS requirements, we expect networks to face problems of congestion and overload that prevent the effective functioning of a radio access network (RAN). This paper proposes a more effective packet‐based scheduling scheme for data traffic by 5G slicing with two operation modes for improving the resource utilization of 5G cloud RAN and providing an efficient isolation of the 5G slices. These two operation modes are referred to as static sharing resource (SSR) scheme and dynamic sharing resources (DSR) scheme. The SSR scheme is a modified version of an existing method. The goal of this approach is to reallocate the shared available resources of 5G network fairly and maximize the utilization of bandwidth while protecting a 5G slice from overwhelming other 5G slices. Throughput and delays of the system model are also discussed to show its performance limits. On the basis of the simulation outcomes, we observed that the proposed DSR scheme outperforms the SSR scheme in terms of provided delay and throughput. In addition, the token bucket parameters together with the assigned capacity weight for each slice can be selected and configured based on the required QoS. Finally, a good estimate for the maximum delay bounds of the slices is provided by the derived theoretical delay bound.     

Resource allocation algorithm for LTE networks using fuzzy based adaptive priority and effective bandwidth estimation

In this paper, we propose a scheme to allocate resource blocks for the Long Term Evolution (LTE) downlink based on the estimation of the effective bandwidths of traffic flows, where users’ priorities are adaptively computed using fuzzy logic. The effective bandwidth of each user traffic flow that is estimated through the parameters of the adaptive β-Multifractal Wavelet Mode modeling, is used to attain their quality of service (QoS) parameters. The proposed allocation scheme aims to guarantee the QoS parameters of users respecting the constraints of modulation and code schemes (modulation and coding scheme) of the LTE downlink transmission. The proposed algorithm considers the average channel quality and the adaptive estimation of effective bandwidth to decide about the scheduling of available radio resources. The efficiency of the proposed scheme is verified through simulations and compared to other algorithms in the literature in terms of parameters such as: system throughput, required data rate not provided, fairness index, data loss rate and network delay.     

Adaptive envelope process and minimum service curve applied to resource block allocation in the LTE downlink

In this work, we propose a resource allocation algorithm for the LTE downlink that makes use of an adaptive multifractal envelope process and a minimum service curve. The proposed scheduling algorithm aims to improve some network parameters while guaranteeing a maximum delay to the user by considering the following information: backlog, channel condition and user traffic behavior. In order to estimate the maximum network delay, we propose an adaptive minimum service curve for the LTE network that can be used for admission control purposes in the resource allocation algorithm. The performance of the proposed scheduling algorithm is compared to those of several scheduling schemes known in the literature through computational simulations of the LTE downlink. In order to develop a new adaptive envelope process and to precisely describe network flows, we propose an adaptive algorithm to estimate the parameters of the Multifractal Wavelet Model (MWM). The proposed envelope process is compared to the main traffic model based envelope processes known in the literature. Simulations of the LTE downlink considering AMC (Adaptive Modulation and Coding) are carried out showing the efficiency of the proposed resource allocation approach that considers adaptive estimation of network traffic parameters.     

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.     

A dynamic fog service provisioning approach for IoT applications

Internet of Things (IoT) is an ecosystem that can improve the life quality of humans through smart services, thereby facilitating everyday tasks. Connecting to cloud and utilizing its services are now public and common, and the experts seek to find some ways to complete cloud computing to use it in IoT, which in next decades will make everything online. Fog computing, where the cloud computing expands to the edge of the network, is one way to achieve the objectives of delay reduction, immediate processing, and network congestion. Since IoT devices produce variations of workloads over time, IoT application services will experience traffic trace fluctuations. So knowing about the distribution of future workloads required to handle IoT workload while meeting the QoS constraint. As a result, in the context of fog computing, the main objective of resource management is dynamic resource provisioning such that it avoids the excess or dearth of provisioning. In the present work, we first propose a distributed computing framework for autonomic resource management in the context of fog computing. Then, we provide a customized version of a provisioning system for IoT services based on control MAPE‐k loop. The system makes use of a reinforcement learning technique as decision maker in planning phase and support vector regression technique in analysis phase. At the end, we conduct a family of simulation‐based experiments to assess the performance of our introduced system. The average delay, cost, and delay violation are decreased by 1.95%, 11%, and 5.1%, respectively, compared with existing solutions.     

Radio resource management for cellular CDMA systems supporting heterogeneous services

A novel radio resource management (RRM) scheme for the support of packet-switched transmission in cellular CDMA systems is proposed by jointly considering the physical, link, and network layer characteristics. The proposed resource management scheme is comprised of a combination of power distribution, rate allocation, service scheduling, and connection admission control. Power distribution allows individual connections to achieve their required signal-to-interference-plus-noise ratio, while rate allocation guarantees the required delay/jitter for real-time traffic and the minimum transmission rate requirement for non-real-time traffic. Efficient rate allocation is achieved by making use of the randomness and burstiness; of the packet generation process. At the link layer, a packet scheduling scheme is developed based on information derived from power distribution and rate allocation to achieve quality of service (QoS) guarantee. Packet scheduling efficiently utilizes the system resources in every time slot and improves the packet throughput for non-real-time traffic. At the network layer, a connection admission control (CAC) scheme based on the lower layer resource allocation information is proposed. The CAC scheme makes use of user mobility information to reduce handoff connection dropping probability (HCDP). Theoretical analysis of the grade of service performance, in terms of new connection blocking probability, HCDP, and resource utilization, is given. Numerical results show that the proposed RRM scheme can achieve both effective QoS guarantee and efficient resource utilization.     

基于多优先级时延预留的接入控制机制

该文提出一种多优先级时延预留的呼叫接入控制机制,通过对不同的优先级业务采用不同的时延门限来控制业务的接入来保证网络服务质量(QoS)。仿真结果表明,该机制不但较好地提供了对高优先级业务的服务率,也保证了对低优先级业务的服务,同时网络利用率也相应得到了提高。     

A resource‐tuned QoS multicast routing protocol

This paper presents a novel framework for quality‐of‐service (QoS) multicast routing with resource allocation that represents QoS parameters, jitter delay, and reliability, as functions of adjustable network resources, bandwidth, and buffer, rather than static metrics. The particular functional form of QoS parameters depends on rate‐based service disciplines used in the routers. This allows intelligent tuning of QoS parameters as functions of allocated resources during the multicast tree search process, rather than decoupling the tree search from resource allocation. The proposed framework minimizes the network resource utilization while keeping jitter delay, reliability, and bandwidth bounded. This definition makes the proposed QoS multicast routing with resource allocation problem more general than the classical minimum Steiner tree problem. As an application of our general framework, we formulate the QoS multicast routing with resource allocation problem for a network consisting of generalized processor sharing nodes as a mixed‐integer quadratic program and find the optimal multicast tree with allocated resources to satisfy the QoS constraints. We then present a polynomial‐time greedy heuristic for the QoS multicast routing with resource allocation problem and compare its performance with the optimal solution of the mixed‐integer quadratic program. The simulation results reveal that the proposed heuristic finds near‐optimal QoS multicast trees along with important insights into the interdependency of QoS parameters and resources.     

RAD‐EI: A routing attack detection scheme for edge‐based Internet of Things environment

Internet of Things (IoT) offers various types of application services in different domains, such as “smart infrastructure, health‐care, critical infrastructure, and intelligent transportation system.” The name edge computing signifies a corner or edge in a network at which traffic enters or exits from the network. In edge computing, the data analysis task happens very close to the IoT smart sensors and devices. Edge computing can also speed up the analysis process, which allows decision makers to take action within a short duration of time. However, edge‐based IoT environment has several security and privacy issues similar to those for the cloud‐based IoT environment. Various types of attacks, such as “replay, man‐in‐the middle, impersonation, password guessing, routing attack, and other denial of service attacks” may be possible in edge‐based IoT environment. The routing attacker nodes have the capability to deviate and disrupt the normal flow of traffic. These malicious nodes do not send packets (messages) to the edge node and only send packets to its neighbor collaborator attacker nodes. Therefore, in the presence of such kind of routing attack, edge node does not get the information or sometimes it gets the partial information. This further affects the overall performance of communication of edge‐based IoT environment. In the presence of such an attack, the “throughput of the network” decreases, “end‐to‐end delay” increases, “packet delivery ratio” decreases, and other parameters also get affected. Consequently, it is important to provide solution for such kind of attack. In this paper, we design an intrusion detection scheme for the detection of routing attack in edge‐based IoT environment called as RAD‐EI. We simulate RAD‐EI using the widely used “NS2 simulator” to measure different network parameters. Furthermore, we provide the security analysis of RAD‐EI to prove its resilience against routing attacks. RAD‐EI accomplishes around 95.0% “detection rate” and 1.23% “false positive rate” that are notably better than other related existing schemes. In addition, RAD‐EI is efficient in terms of computation and communication costs. As a result, RAD‐EI is a good match for some critical and sensitive applications, such as smart security and surveillance system.     

车联网中网络切片资源分配方案

为了满足车联网中不同应用的服务质量(Quality of Service, QoS)要求,提出了一种基于网络切片技术的车联网频谱资源分配方案。该方案考虑数据接入控制,通过联合优化频谱资源块(Resource Block, RB)分配和车辆信号发射功率控制,在安全服务切片低时延高可靠性的约束下,最大化信息娱乐服务切片的平均和吞吐量。将车联网资源管理建模为一个混合整数随机优化问题,利用李雅普诺夫(Lyapunov)优化理论将该优化问题分解为接入控制和RB分配与功率控制两个子问题,并分别对其进行求解,得到每个时隙的接入控制和资源分配方案。仿真结果表明,所提出的资源分配方案能够有效提高信息娱乐服务切片的平均和吞吐量,并且可以通过调整引入的控制参数值来实现吞吐量和时延的动态平衡。同时,与已有方案相比,该方案具有更好的时延性能。     

Buffer-aware resource scheduling scheme for LTE-A uplink relay-assisted network

Due to the constraint of single carrier frequency division multiple access （SC-FDMA） adopted in long term evolution （LTE） uplink, subcarriers allocated to single user equipment （UE） must be contiguous. This contiguous allocation constraint limits resource allocation flexibility and makes the resource scheduling problem more complex. Most of the existing work cannot well meet UE＇s quality of service （QoS） requirement, because they just try to improve system performance mainly based on channel condition or buffer size. This paper proposes a novel resource scheduling scheme considering channel condition, buffer size and packet delay when allocating frequency resource. Firstly, optimization function is formulated, which aims to minimize sum of weight for bits still left in UE buffer after each scheduling slot. QoS is the main concern factor here. Then, to get packet delay information, this paper proposes a delay estimation algorithm. Relay node （RN） is introduced to improve overall channel condition. Specific RN selection strategy is also depicted in the scheme. Most important of all, a creative negotiation mechanism is included in the subcarrier allocation process. It can improve the overall system throughput performance in guarantee of user＇s QoS requirement. Simulation results demonstrate that the scheme can greatly enhance system performance like delay, throughput and jitter.     

一种基于无线多媒体业务的可升降级QoS动态带宽分配与优化策略

无线多媒体网络中的业务包括话音、流媒体、交互类和背景类业务4种,除话音业务外其余3种业务都是可变比特速率业务。对该网络用户资源分配(主要是带宽的分配)若采用传统的固定分配方法,必定陷入资源利用率低下和用户QoS得不到保障的两难境地。该文提出了一种基于无线多媒体业务的动态带宽分配与优化策略,在保证用户QoS的前提下,尽可能提高资源利用率。该文分别从网络和用户两个角度考虑,通过系统容量、业务阻塞率、数据延迟、流媒体的实际传输比和VBR业务综合服务等级等参数,对可升降级QoS无线多媒体网络进行了仿真分析,结果表明,对比传统的网络资源管理策略,该策略大大改善了系统的性能,提高了系统资源利用率。     

Efficient Resource Allocation for Policy-Based Wireless/Wireline Interworking

This paper proposes efficient resource allocation techniques for a policy-based wireless/wireline interworking architecture, where quality of service (QoS) provisioning and resource allocation is driven by the service level agreement (SLA). For end-to-end IP QoS delivery, each wireless access domain can independently choose its internal resource management policies to guarantee the customer access SLA (CASLA), while the border-crossing traffic is served by a core network following policy rules to meet the transit domain SLA (TRSLA). Particularly, we propose an engineered priority resource sharing scheme for a voice/data integrated wireless domain, where the policy rules allow cellular-only access or cellular/WLAN interworked access. By such a resource sharing scheme, the CASLA for each service class is met with efficient resource utilization, and the interdomain TRSLA bandwidth requirement can be easily determined. In the transit domain, the traffic load fluctuation from upstream access domains is tackled by an inter-TRSLA resource sharing technique, where the spare capacity from underloaded TRSLAs can be exploited by the overloaded TRSLAs to improve resource utilization. Advantages of the inter-SLA resource sharing technique are that the core network service provider can freely design the policy rules that define underload and overload status, determine the bandwidth reservation, and distribute the spare resources among bandwidth borrowers, while all the policies are supported by a common set of resource allocation techniques.     

Jitter‐minimized reliability‐maximized management of networks

We propose a joint optimization network management framework for quality‐of‐service (QoS) routing with resource allocation. Our joint optimization framework provides a convenient way of maximizing the reliability or minimizing the jitter delay of paths. Data traffic is sensitive to droppage at buffers, while it can tolerate jitter delay. On the other hand, multimedia traffic can tolerate loss but it is very sensitive to jitter delay. Depending on the type of data, our scheme provides a convenient way of selecting the parameters which result in either reliability maximization or jitter minimization. We solve the optimization problem for a GPS network and provide the optimal solutions. We find the values of control parameters which control the type of optimization performed. We use our analytical results in a multi‐objective QoS routing algorithm. Finally, we provide insights into our optimization framework using simulations. Copyright © 2011 John Wiley & Sons, Ltd.     

QoS Provisioning with New Effective Bandwidth/Buffer Calculation Scheme in Wireless IP Networks

The huge commercial success of mobile telephony, the phenomenal growth of Internet users, the popularity of IP-based multimedia applications are the major driving forces behind third-generation (3G), ongoing Byond 3G (B3G), and forth-genertion (4G) evolution. 3G brought wired applications, both data and multimedia, into wireless environments. It operates on IP-based infrastructures to provide wider service access capability. To support and satisfy QoS (Quality of Service) of diverse IP-based multimedia applications, traffic management, such as Connection Admission Control (CAC) and resource allocation, becomes essential. CAC and resource allocation are computationally complex when combined with QoS guarantee for traffic with different characteristics. However, CAC and resource allocation are real-time traffic control procedures. Hence, processing load should be minimized to reduce delay. At the same time, network resources should be utilized efficiently to accommodate more users. However, reducing processing load and obtaining high resource utilization efficiency has been considered to be contradictory matter. In addition, CAC and resource allocation schemes which consider multiple QoS criteria – loss and delay – simultaneously have not been adequately studied. Simultaneous QoS consideration is important to satisfy stringent and diverse QoS requirements of multimedia traffic. In this paper, we propose a nobel effective bandwidth/buffer calculation method based on a virtual channel/buffer analysis scheme. We show that our method can achieve high resource utilization efficiency with reduced processing load. Moreover, we show that our scheme allows for simultaneous consideration of multiple QoS criteria, loss and delay.     

Low Complexity Modified Viterbi Decoder with Convolution Codes for Power Efficient Wireless Communication

To attain high quality of service (QoS) with efficient power consumption with minimum delay through Wireless Local Area Network (WLAN) through mesh network is an important research area. But the existing real-time routing system involves multiple hops with time varying mobility channels for fastest data propagation is greatly degraded with power utilization factor through congestion traffic queue. Required allocation and resource management through desired access points plays vital roles in which multiple hops demands delay rates by interconnected data nodes. In order to achieve high throughput with minimum delay the QoS in real-time data communication have to be concentrated by using Viterbi decoder with convolution codes. By undertaking IEEE 802.11 WLAN physical layers afford multiple transmission rates by engaging various modulations and channel coding schemes, major point arises to pinpoint the desired transmission rate to enhance the performance. Because each node exhibits different dynamic characteristics based on the token rings passed from the server to the end links. In order to validate the real-time traffic with power consumption and average delay communication, an improved Viterbi decoder is designed with convolution codes to determine accurate channel estimation based on learning the utilization ration of the needed to execute the current wireless channel optimization. The proposed methodology can attain accurate channel estimation without additional implementation effort and modifications to the current 802.11 standard. And each node is capable to choose the optimized transmission rate, so that the system performance can be improved with very minimum power with high packet transmission ratio with minimum traffic rate to improve QoS. The proposed scheme also offers an appealing combination of the allocation of transmission rate and the current link condition. Based on the basic relationship between them, the proposed decoding scheme maximizes the throughput with periodic learning of channel variation and system status.

     

Quality-driven cross-layer optimized video delivery over LTE

3GPP Long Term Evolution is one of the major steps in mobile communication to enhance the user experience for next-generation mobile broadband networks. In LTE, orthogonal frequency- division multiple access is adopted in the downlink of its E-UTRA air interface. Although cross-layer techniques have been widely adopted in literature for dynamic resource allocation to maximize data rate in OFDMA wireless networks, application-oriented quality of service for video delivery, such as delay constraint and video distortion, have been largely ignored. However, for wireless video delivery in LTE, especially delay-bounded real-time video streaming, higher data rate could lead to higher packet loss rate, thus degrading the user-perceived video quality. In this article we present a new QoS-aware LTE OFDMA scheduling algorithm for wireless real-time video delivery over the downlink of LTE cellular networks to achieve the best user-perceived video quality under the given application delay constraint. In the proposed approach, system throughput, application QoS constraints, and scheduling fairness are jointly integrated into a cross-layer design framework to dynamically perform radio resource allocation for multiple users, and to effectively choose the optimal system parameters such as modulation and coding scheme and video encoding parameters to adapt to the varying channel quality of each resource block. Experimental results have shown significant performance enhancement of the proposed system.     

Fair resource allocation with guaranteed statistical QoS for multimedia traffic in wideband CDMA cellular network

A dynamic fair resource allocation scheme is proposed to efficiently support real-time and non-real-time multimedia traffic with guaranteed statistical quality of service (QoS) in the uplink of a wideband code-division multiple access (CDMA) cellular network. The scheme uses the generalized processor sharing (GPS) fair service discipline to allocate uplink channel-resources, taking into account the characteristics of channel fading and intercell interference. In specific, the resource allocated to each traffic flow is proportional to an assigned weighting factor. For real-time traffic, the assigned weighting factor is a constant in order to guarantee the traffic statistical delay bound requirement; for non-real-time traffic, the assigned weighting factor can be adjusted dynamically according to fading, channel states and the traffic statistical fairness bound requirement. Compared with the conventional static-weight scheme, the proposed dynamic-weight scheme achieves capacity gain. A flexible trade-off between the GPS fairness and efficient resource utilization can also be achieved. Analysis and simulation results demonstrate that the proposed scheme enhances radio resource utilization and guarantees statistical QoS under different fairness bound requirements.