Security-Aware Distributed Service Composition for Wireless Sensor Networks Based Smart Metering in Smart Grid Using Software Defined Networks

Smart grid (SG) network is one of the recently improved networks of tangled entities, objects, and smart metering infrastructure (SMI). It plays a vital part in sensing, acquiring, observing, aggregating, controlling, and dealing with various kinds of fields in SG. The SMI or advanced metering infrastructure (AMI) is proposed to make available a real-time transmissions connection among users and services are Time of use (TOU), Real time pricing (RTP), Critical Peak Pricing (CPP). In adding to, additional benefit of SMs is which are capable to report back to the service control center in near real time nontechnical losses (for instance, tampering with meters, bypassing meters, and illicit tapping into distribution systems). SMI supports two-way transmission meters reading electrical utilization at superior frequency. This data is treated in real time and signals send to manage demand. This paper expresses a transitory impression of cyberattack instances in customary energy networks and SMI. This paper presents cyber security attacks and countermeasures in Smart Grid Metering Network (SGMN). Based on the existing survey threat models, a number of proposed ways have been planned to deal with all threats in the formulation of the secrecy and privacy necessities of SG measurement network.

The purpose of the paper is to examine if public long term evolution (LTE) network is suitable for smart grid (SG) automatic metering usage, in a suburban scenario, without causing significant hindrance to typical LTE traffic. In addition, the same generalized suburban scenario is evaluated with a hybrid sensor - LTE network where wireless sensor network (WSN) cluster heads are also equipped with LTE remote terminal units (RTUs). The simulation topology is formed as a suburban area that consists of single RTU per apartment/house for SG traffic and an average 3.7 people per habitat, each with their user equipment, using one of the available carriers. Normal SG traffic is generated in both directions, uplink and downlink. The worst-case usage factor is considered as a power outage, where all SG meters in the area of influence simultaneously detect and attempt to report such a failure. Thus, emergency SG traffic is generated simultaneous by all RTUs. To alleviate the problem of the high momentary SG emergency traffic load, two distinct solutions are proposed and simulated. As the first solution, an artificial, up to one-second random delay is introduced in the transmission scheduling of emergency messages. The second solution applies low-power WSNs at the cluster level and cluster heads that contain both 802.15.4 and LTE communication interfaces, i.e., a hybrid sensor-LTE network. The simulation results show that both of the solutions that try to alleviate the high instantaneous traffic loads can reach the quality of service criteria for SG traffic without compromising other public LTE traffic. The deciding factor to use either pure LTE approach or a hybrid sensor-LTE network comes from non-functional requirements of the system.

Wireless multimedia sensor and actor networks for the next generation power grid

WSNs (Wireless Sensor Networks) have been considered one of the very promising technologies for the implementation of smart grid. And security of WSNs becomes a central concern. The security solutions for generic wireless sensor networks cannot be directly used in smart grid WSNs. In this paper, the applications of sensor networks in electric power systems are discussed and analyzed first. Then, the characteristics of smart grid WSNs are summarized. Threats and security requirements special for wireless sensor networks used in smart grid systems are presented. Based on these works, reference security architecture was proposed to guide the development and the design of the security solutions of wireless sensor networks in smart grid systems, considering the information security requirements of electric power systems. Moreover, open security issues needed solve to protect WSNs applied in smart grid, and research challenges are introduced.

In today’s scenario, the Internet has dominated almost all domains. It led to revolutionary advancements in the existing technology by conceptualizing the ordinary power grid into a smart grid. Use of smart meters, sensors and other gadgets in the smart grid has made the existing cyber-physical system more resilient and efficient than the existing one. By the aid of the Internet, the components of the smart grid are connected to the same server. This paper emphasizes the importance of communication between the elements of the grid. A successful communication system allows the transfer of information and energy between the components of the grid. Components like wireless sensor networks (WSN) are useful for such networks. Along with an energy management unit, they can control the load demand of a consumer. The load demand is smartly shifted from peak hours to off-peak hours, following the concept of time of usage (TOU) pricing. Due to this shift in demand, the user has to pay a lesser amount for energy. This paper presents a unique approach based on devices which are easy to access. A case study is presented wherein data is transmitted via communication established between devices. The WSN and EMU smartly adjust the load in off-peak durations. A drop in the bill of the user is seen. This can be further extended for industries and other power system networks.

Appliance Identification Based on Smart Meter Data and Event-Driven Processing in the 5G Framework

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

In smart grid, Advanced Metering Infrastructure (AMI) systems feed the metering data to Energy Supplier (ES) every 15 minutes. Using this information, ES can offer incentives to reduce the total power consumption during the peak hours through the real-time pricing mechanism. However, it also brings privacy concerns. Since the metering data is collected by the ES nearly in real-time, the customer's behavior and habits can be disclosed via the statistical patterns. The privacy problem will hamper the development and deployment of future smart grid. In this paper, we propose a novel metering data transmission scheme in wireless networks. In each Smart Meter (SM), the metering data is split into two parts randomly: Part 1 and Part 2, where the sum of two parts is equal to the original metering data. Part 1 is sent to the ES via cellular link, and Part 2 is sent to the next SM via Wireless Sensor Network (WSN) link. Then the next SM merges Part 2 of the previous SM into its original metering data, and creates the updated metering data. Using the proposed scheme, the metering data received by the ES is randomized, and the customer's privacy can be effectively protected even if some SM cooperates with the ES.

Reducing the power supply-demand gap and increasing reliability of power supply are the challenges of current energy management. Implementation of smart grid, smart meters and smart metering can be a possible solution for power demand reduction, efficient power supply management, and optimization of management resource usages. Smart meters include sophisticated measurement and calculation hardware, software, calibration and communication capabilities. For interoperability within a smart grid infrastructure, smart meters are designed to perform functions, and store and communicate data according to certain standards. In this work we discuss smart meter and various elements of smart metering, current state of the technologies related to smart grid, smart meter, advanced metering infrastructure (AMI), and meter data flow in smart grid. We also discuss standards related to smart meter, meter data format and data transmission, functions of smart meter, and functionalities of smart meters, currently deployed by utilities around the world.

Wireless Sensors Networks (WSNs) have been gaining significant attention in both the industries and the academia in recent years. However, WSN are vulnerable to growing security threats and attacks which are inept for the current traditional security mechanisms to cope with or mitigate such security challenges. As a solution, Software Defined Network (SDN) has emerged and been merged with WSN to form what is known as Software Defined Wireless Sensor Network (SDWSN). SDWSN is introduced to bring flexibility, programmability and innovation to the WSN network. However, SDWSN is not exempted from security challenges. SDWSN is faced with multitude of security challenges inherited from both SDN and WSN which have become a bottle-neck to its operations and applicability. Therefore, this paper presents security challenges in both WSN and SDN which are transferable to SDWSN. We discussed the inheritable security challenges from the perspective of SDN and WSN by outlining several possible threats, attacks and some countermeasures. This is important to bring together these challenges in order to attract or stimulate more research and development activities aim at realizing a more secure and dependable SDWSN.

Wireless Sensor Networks (WSNs) have a wide range of applications scenarios in computer vision, from pedestrian detection to robotic visual navigation. In response to the growing visual data services in WSNs, we propose a proactive caching strategy based on Stacked Sparse Autoencoder (SSAE) to predict content popularity (PCDS2AW). Firstly, based on Software Defined Network (SDN) and Network Function Virtualization (NFV) technologies, a distributed deep learning network SSAE is constructed in the sink nodes and control nodes of the WSN network. Then, the SSAE network structure parameters and network model parameters are optimized through training. The proactive cache strategy implementation procedure is divided into four steps. (1) The SDN controller is responsible for dynamically collecting user request data package information in the WSNs network. (2) The SSAEs predicts the packet popularity based on the SDN controller obtaining user request data. (3) The SDN controller generates a corresponding proactive cache strategy according to the popularity prediction result. (4) Implement the proactive caching strategy at the WSNs cache node. In the simulation, we compare the influence of spatiotemporal data on the SSAE network structure. Compared with the classic caching strategy Hash + LRU, Betw + LRU, and classic prediction algorithms SVM and BPNN, the proposed PCDS2AW proactive caching strategy can significantly improve WSN performance.

An efficient dependable smart power grid relies on the secure real-time data collection and transmission service provided by a monitoring system. In such a system, the measuring units, such as phasor measurement units (PMUs) and smart meters (SMs), are critical. These measuring equipments function as sensors in the smart grid. Data exchanges between these sensors and the central controller are protected by various security protocols. These protocols usually contain computationally intensive cryptographic algorithms that cause heavy energy overhead to the sensor nodes. Since PMUs and SMs are mostly energy-constrained, the problem of how to ensure the secure communication with minimum energy cost becomes a critical issue for the functionality of the whole smart grid. In this article, we focus on the low power secure communication of the PMUs and SMs. We take two wireless sensor platforms as examples to experimentally investigate the approaches and principles of reconciling the two conflicting system requirements-communication security and low energy consumptions. The proposed methods are general ones and applicable to other energy-constrained yet security sensitive systems.

Smart metering is one of the most important infrastructures of the Smart Grid. It is based on intelligent measurement using smart meters, wireless sensor networks, remote networks for the bidirectional exchange of measurement data and the supervision center which allows the control, the treatment and the intelligent management of measurement data. Smart metering is designed to allow the consumer to pilot his level of consumption in order to reduce it by the intelligent control of electronic devices of his home automation whose objective is to economize the use of electricity within a smart home. On the other hand, it is deployed by power service utilities through the advanced measurement infrastructure provided by smart readers to provide remote monitoring of large-scale consumers in a reliable and efficient manner. It works without reading errors due to the displacement of staff to view consumption levels from traditional meters and without using an estimation of consumption level from the history. It allows service and energy operators to manage the supply in a more reliable and intelligent way according to the balance between autonomous production and consumption and according to the geographical area which improves the services of the grid intelligent in the context of meeting the requirements of users and ensuring the safety of the entire electrical system.

In Wireless Sensor Network (WSN), resource optimization is one of the challenging issues. It improves the network performance. This can be achieved with the help of a new networking technology, called Software Defined Networking (SDN). The concept of SDN is to decouple the control plane from the forwarding plane of a network to improve the performance of the networking applications. Traffic Engineering (TE) is a domain of network applications that manages the network traffic, and try to optimize the network resources. SDN offers multiple features to support TE applications. SDN combined with WSN forms a new networking domain called Software Defined WSN (SDWSN). Since WSN has resource-constrained nodes, resource optimization is a need in WSN. This paper proposes an optimized link utilization based approach for TE in SDWSN. The proposed approach discusses about a traffic optimization algorithm, called Optimized Link Allocation based TE (OLA-TE). OLA-TE is implemented at the controller node and helps to improve the overall network utilization. The SDN sensor nodes find the optimized path for traffic routing with the help of controller node. The proposed approach is compared with the traditional WSN approach. IBM CPLEX Optimization Studio and MATLAB are used for validation purposes. The CPLEX results assure a network flow-cost optimization of about 10%. The results of MATLAB show that despite having extra control traffic on network, the network performance gets improved over the period of time.

Energy efficiency is one of the key requirements in Wireless Sensor Networks (WSNs). In order to optimize energy usage at sensor nodes, this paper proposes a new WSN architecture that relies on concepts of Software Defined Networking (SDN). Since SDN is a relatively new technology, originally envisioned for wired networks, it can't be expected to get immediately adopted in WSN domain, regardless of potential benefits. For this reason, we consider scenario where SDN nodes coexist with traditional sensor nodes, and propose a new routing algorithm for SDN controller that prolongs the WSN lifetime even when small percentage of SDN nodes is deployed.