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.     

Machine learning for internet of things data analysis: a survey

Rapid developments in hardware, software, and communication technologies have facilitated the emergence of Internet-connected sensory devices that provide observations and data measurements from the physical world. By 2020, it is estimated that the total number of Internet-connected devices being used will be between 25 and 50 billion. As these numbers grow and technologies become more mature, the volume of data being published will increase. The technology of Internet-connected devices, referred to as Internet of Things (IoT), continues to extend the current Internet by providing connectivity and interactions between the physical and cyber worlds. In addition to an increased volume, the IoT generates big data characterized by its velocity in terms of time and location dependency, with a variety of multiple modalities and varying data quality. Intelligent processing and analysis of this big data are the key to developing smart IoT applications. This article assesses the various machine learning methods that deal with the challenges presented by IoT data by considering smart cities as the main use case. The key contribution of this study is the presentation of a taxonomy of machine learning algorithms explaining how different techniques are applied to the data in order to extract higher level information. The potential and challenges of machine learning for IoT data analytics will also be discussed. A use case of applying a Support Vector Machine (SVM) to Aarhus smart city traffic data is presented for a more detailed exploration.     

基于指令虚拟化的安卓本地代码加固方法

安卓系统越来越广泛地被应用于各种类型的智能设备,比如智能手机、智能手表、智能电视、智能汽车。与此同时,针对这些平台应用软件的逆向攻击也日益增多,这不仅极大地侵犯了软件开发者的合法权益,也给终端用户带来了潜在的安全风险。如何保护运行在各种类型设备上的安卓应用软件不被逆向攻击成为一个重要的研究问题。然而,现有的安卓软件保护方法比如命名混淆、动态加载、代码隐藏等虽然可在一定程度上增加安卓软件的逆向难度,但是原理相对简单容易被绕过。一种更为有效的方法是基于指令虚拟化的加固方法,但已有的指令虚拟化方法只针对特定架构(x86架构),无法兼容运行于多种架构的安卓设备。该文针对安卓应用软件中的本地代码提出了一种架构无关的指令虚拟化技术,设计并实现了基于虚拟机打包保护(VMPP)的加固系统。该系统包含一套基于寄存器架构的定长虚拟指令集、支持该虚拟指令集的解释器以及可以与现有开发环境集成的工具链。在大量C/C++代码以及真实安卓软件上的测试表明,VMPP在引入较低的运行时开销下,能够显著提升安卓本地代码的防逆向能力,并且可被用于保护不同架构上的安卓本地代码。     

Optimal Resource allocation in NOMA‐based M2M communication using Hybrid Rider Optimization with FireFly: Power Saving Strategy of IoT

Nowadays, the Orthogonal Multiple Access (OMA) principle has utilized for allocating proper radio resources in wireless networks. However, as the count of users rises, OMA‐based approaches may not satisfy the stringent emerging requirements including very low latency, very high spectral efficiency, and massive device connectivity. Moreover, there are significant challenges in cellular‐enabled Machine‐to‐Machine (M2M) communications due to the unique features of M2M‐based applications. In order to overwhelm these challenges, non‐orthogonal multiple access (NOMA) principles emerge as a solution to enhance the spectral efficiency while allowing some degree of multiple access interference at receivers. Hence, this paper intends to develop an optimal resource allocation mechanism for M2M communication. Here, the nonlinear energy harvesting performed with the aid of an accessing technology termed as NOMA. The key objective of the proposed resource allocation model is the minimization of the total energy consumption of the network. For attaining the minimized power consumption, the time allocation, and transmission power of NOMA is optimally tuned by a hybrid optimization algorithm. The proposed hybrid algorithm merges the beneficial concepts of Rider Optimization Algorithm (ROA) and FireFly (FF) algorithm and implements a new algorithm termed as FireFly Modified Bypass‐based Rider Optimization Algorithm (FMB‐ROA). Finally, the analysis of total energy concerning various constraints validates the performance of the proposed model over conventional models.     

Use of the smart technology for water quality control: feedback from large-scale experimentation

The main purpose of drinking water network is to ensure safe quality of water to users. However, accidental contamination and malicious attacks in water networks can degrade the water quality. Such critical events threat the human health and lead to harmful diseases. Water utilities are concerned by the control of water quality. Since conventional methods based on laboratory analyses require several days, online control technology presents good opportunity to rapid detection of any water contamination. Devices based on smart technology have been developed for real-time control of the water quality. However, the use of these devices is recent and yet requires investigations. This paper presents feedback of the use of the smart technology in a large-scale experimentation conducted at the campus of Lille University within the European project “SmartWater4Europe”. Two devices are used: S::CAN, which measures various parameters such as Conductivity and Turbidity and EventLab, which measures the variation of the refractive index. This paper presents the implementation of these devices, data storage and management as well as analysis of recorded data.     

Feasibility and Fundamental Limits of Energy-Harvesting Based M2M Communications

Energy-efficient, reliable and scalable machine-to-machine (M2M) communications is the key technical enabler of Internet-of-Things (IoT) networks. Furthermore, as the number of populated devices is constantly increasing, self-sustaining or energy-autonomous IoT nodes are a promising prospect receiving increasing interest. In this paper, the feasibility and fundamental limits of energy harvesting based M2M communication systems are studied and presented. The derived theoretical bounds are effectively based on the Shannon theorem, combined with selected propagation loss models, assumed link nonidealities, as well as the given energy harvesting and storage capabilities. Fundamental limits and available operational time of the communicating nodes are derived and analyzed, together with extensive numerical results evaluated in different practical scenarios for low power sensor type communication applications.     

M2M小数据业务的IEEE 802.11WLAN分析模型

机器对机器(M2M,machine to machine)通信有着巨大的市场潜力,无线局域网(WLAN)作为3G网络的主要补充必将承载大量M2M业务。针对具有时延容忍、耐性重试等特点的典型的M2M小数据业务,提出了一种大时间尺度退避的IEEE 802.11 DCF网络分析模型,推导了MAC层服务时间的概率分布;建立IPP/G/1/K离散时间排队系统模型,研究了非饱和负载下M2M业务在WLAN非理想信道中传输的QoS性能。算法仿真结果表明,大时间尺度退避机制有效提高了系统的吞吐量,降低了系统阻塞率。     

Infrastructure for Intelligent Automation Services in the Smart Grid

The electricity grid is undergoing a radical transformation from a production-driven to a demand-driven energy delivery platform known as the smart grid. The integration of a large amount of renewable and distributed energy resources, together with new patterns of electricity production, accentuates the need for research in information and communication technologies to control bi-directional energy flows. The European FP7 project: “Energy Demand Aware Open Services for Smart Grid Intelligent Automation” is contributing to this research by providing an intelligent infrastructure for service deployment for the smart grid. The project defines a system architecture that provides interoperability between wireless sensors in home area networks connected over the Internet to a service provider function deployed in a cloud infrastructure. A key component in this infrastructure is the Home Energy Controlling Hub that, on the one hand, provides a platform for monitoring and aggregation of electricity consumption data from devices and appliances and, on the other hand, is the link between the deployed intelligent automation services and the home. To ensure openness and simplicity, the proposed infrastructure is based on the representational state transfer style architecture. This is adopted by implementing the emerging ZigBee IP and Smart Energy Profile 2.0 standards that to a wide extend conform with the Internet Protocol suite and state-of-the art web services development.     

M2M energy saving strategy in 5G millimeter wave system

Telecommunication Systems - Machine to Machine technology has a broad application prospect in the 5G network, but there is a bottleneck in the energy consumption of intelligent devices powered by...     

Reliable and secure data transfer in IoT networks

With the rapid technological improvements in mobile devices and their inclusion in Internet of Things (IoT), secure key management becomes mandatory to ensure security of information exchange. For instance, IoT applications, such as smart health-care and smart homes, provide automated services to the users with less or no user intervention. As these application use user-sensitive data, ensuring their security and privacy should be paramount, especially during the key management process. However, traditional approaches for key management will not suit well in IoT environment because of the inherent resource constraint property of IoT devices. In this paper, we propose a novel distributed key management scheme for IoT ecosystem. The proposed scheme efficiently provides security to IoT devices by delegating most of the resource consuming cryptographic processing to a local entity. This entity coordinates with other peer entities to provide a distributed key as well as an authentication mechanism to network devices. In particular, the proposed scheme exploits the advantages of mobile agents by deploying them in different subnetworks as and when required: (1) to process the cryptography work for the IoT devices, and (2) to act as an local authenticated entity to perform fast authentication process. To verify the effectiveness and correctness of our proposed scheme, we have simulated it in a large IoT scenario and evaluated against relevant metrics that includes user mobility, certification generation time, and communication overhead.

     

Model for autonomous agents in machine‐to‐machine navigation networks

Machine‐to‐machine (M2M) is an evolving architecture and tends to provide enormous services through the swarm presence of the networked devices. Localization is one of those services. Previous localization techniques require complex computation that is not suitable and affordable in such architecture. Moreover, integrating intelligent multiagents on these ubiquitous devices makes the network more independent and reactive requiring for a less complex localization model. This paper reviews the present localization techniques and discusses their infeasibility for M2M communication while proposing a mathematical model that is derived from Anderson model for the distributed structure of machine‐type‐communication network involving autonomous agents. This paper has made an attempt to use the property of Anderson model that structures the distributed objects. This paper also classifies autonomous agents according to their functionalities in a navigational network. Recently, Anderson model have been customized for implication of optical communication; in this paper, the proposed mathematical model involves intelligent agents for localization that aim to reduce complexity of positioning computations for nodes having restricted computational resources and battery life, which are the main characteristics of M2M communication.     

Power-efficient routing schemes for MANETs: a survey and open issues

Ubiquitous smart devices with embedded sensors are paving the way for mobile ad hoc networks (MANETs) that enable users to communicate directly, thereby playing a key role in Smart City and Internet of Things applications. In such smart environments, people with smart devices (nodes) can freely self-organize and form self-configuring MANETs to send and forward data packets to a destination over multiple hops via intermediate nodes. However, the energy consumption during routing remains a challenge in such ensemble mobile environments due to the limited battery capacity of mobile devices. This challenging issue has received substantial research attention, necessitating an exhaustive literature search over the variety of academic fields addressing this topic. The main motivation of this paper is to review various power-efficient routing schemes in MANETs that have recently been proposed to reduce the energy consumed when transmitting and receiving packets during active communication. Accordingly, these protocols are classified into six categories: (1) link state-based, (2) source-initiated-based, (3) transmission power control-based, (4) load-balancing-based, (5) location-based and (6) multicast-based routing approaches. The review covers various state-of-the-art protocols for each category and highlights their operation concepts, design challenges and key features. In addition, the various protocols are compared with emphasis on the merits and drawbacks as well as the considered metrics of each scheme. Finally, we provide a conclusion and suggest potential directions for future research in the field.     

基于云服务实现智能家居应用控制的方案

智能家居设备如何接入网络,智能控制终端如何控制智能家居设备,智能家居设备及应用管理平台如何对用户和设备进行管理,这些问题的解决方案伴随着智能家居应用的快速发展不断变化。首先讨论了智能家居业务的应用控制方式,然后引出应用控制的关键逻辑分层结构,在关键逻辑分层结构的基础上,讨论基于云服务的应用控制方案,最后给出总结。     

Physical layer architectures for machine type communication networks—a survey

Machine‐type communication (MTC) has attracted much attention due to the fact that it provides pervasive connections for billions of MTC devices, forming a basis for the Internet of things. Most works in the literatures on machine‐to‐machine (M2M) communications focused on media access layer (MAC) layer or other upper layer applications, such as e‐health, energy management and entertainment services. On the other hand, physical (PHY) layer plays a pivotal role in M2M communications. To accommodate a large number of MTC devices, M2M should be made efficient enough in terms of its power consumption and spectrum utilisation. Copyright © 2016 John Wiley & Sons, Ltd.     

智慧城市关键技术研究

探讨了城市智能管理运行架构、城市泛在感知设施、机器通信能力提升技术、数据共享和活化技术等关键技术。认为巨系统要形成良好的生态体系和自我成长机制,关键技术的突破和相关技术的综合运用都至关重要。关键技术的突破和相关技术的综合运用才能推动智慧城市建设的深入开展和演进。     

移动网络触发M2M终端的技术方案

运营商在M2M业务运营中发现一些业务具有一个共同的特性,就是服务提供商需要触发终端来上传一些数据。现阶段的移动分组网络是为人与人通信设计的,主要提供终端上网络的服务,不具备触发终端的能力。本文介绍了3GPP提出的网络触发终端的几种主要实现方案,在分析不同实现方案应用场景及其优缺点的情况下,指出了可以分阶段使用不同的方案...     

机器对机器通信中一种基于能量效率与系统容量的多目标无线资源管理算法

机器对机器(M2M)通信和设备到设备(D2D)通信都是5G中的关键技术。而M2M通信特别需要考虑提高设备的能量效率(EE)以延长设备的生存周期。该文将M2M技术与D2D技术相结合,考虑M2M设备使用D2D技术进行通信,同时M2M设备复用蜂窝网络中的人对人(H2H)通信的频谱资源。为了同时保证两种系统的服务质量(QoS)需求,建立了最大化M2M的能量效率,最大化H2H系统容量和,以及最小化M2M系统对H2H系统干扰的多目标优化问题(MOOP)。为了解决该问题,采用惩罚函数的方法将二进制变量松弛约束,进而采用凹凸过程(CCCP)方法将非凸的单目标优化问题转化为凸优化问题,并最终通过加权切比雪夫算法得到原多目标优化问题的Pareto最优解。通过与传统的加权和算法进行比较,仿真结果证明了该算法的有效性。     

M_2M_4信噪比估计法在散射通信中的应用

信噪比(SNR)估计对散射通信中功率自适应控制、速率自适应切换及统计信道特性具有重要意义,散射通信需要接收信号的精确信噪比作参考。介绍了一种运算简单、便于工程实现的盲估计算法即二阶矩四阶矩(M2M4)信噪比估计法的原理,将此算法通过硬件来实现。根据散射通信特点,对其进行一系列测试,通过对测试结果分析,得出了M2M4信噪比估计算法在散射通信具有适用性。     

Software defined radio architecture for cellular networks base stations: TheSunbeam project

With the arrival of 3G radio mobile communications standards namelyUmts, new requirements arose for the wireless cellular networks. They concern the quality of the transmissions, the compatibility with pre-existing 2G networks and between different 3G networks and of course the increasing bandwidth to bring new high data rate demanding services through IP connections. TheSunbeam project was at the convergence of two key enabling technologies for 3G: software radio and smart antennas. Software radio appears to be an unavoidable approach to fulfil these specifications, but it needs to be used with new hardware architectures designed to support it.Acts European projectSunbeam just covered partially this subject as it concerned flexible multi-standard smart CBTS architecture study in the context of the migration of European networks from 2G (Gsm, Dcs 1800) to 3 G (Acts/Fdd, Acts/Tdd), concentrating on the physical layer. Digital smart antennas techniques were central in the scope ofSunbeam, since they are to bring the decisive performance improvements 3G transmissions require. This paper summarises the essential results achieved within the project and makes an attempt to establish global specifications for CBTS architecture design to achieve the flexibility, the reconfigurability and the scalability needed to implement software radio.     

基于LTE-230M的合肥电力无线专网建设分析

阐述合肥电力无线专网建设项目,分析合肥220 kV莲花、紫云变以及集控中心等地区的LTE-230M专网建设条件。经过严格的基站选址和设备分析,凭借LTE-230M系统覆盖面积广、建设成本低的特点,计划在合肥建设LTE-230M系统。与传统通信网络相比,LTE-230M系统优势明显,符合智能电网的发展需求。