Analytical performance analysis of a large-scale RF-mesh smart meter communication system

Driven by the information age, a paradigm shift is starting to occur in the urban water planning and management field, mainly due to the introduction of advanced metering and communications technologies. This chapter explores the potential role of intelligent water metering systems, and the smart application of resultant data sets for the future of water planning and management in the built environment. Intelligent water meters essentially perform three functions; they automatically and electronically capture, collect and communicate up-to-date water usage readings on a real-time (or nearly real-time) basis. To translate this data into useful information, a comprehensive intelligent water metering system is required, which integrates high-resolution metering (e.g., 0.01?l; 5?sec), communication technologies (e.g., GPRS) and information management systems, in order to provide real-time information on how, when and where water is being consumed for the customer and water business. This chapter seeks to promote the uptake and application of intelligent water metering systems by examining the benefits and drivers of, and barriers to, intelligent metering. Specifically, it presents applicable examples of where intelligent metering systems can significantly enhance current activities in terms of citywide urban planning, infrastructure planning, water demand management and customer satisfaction.

The utility companies and the researchers have been developing new applications and communication protocols for the Smart Grid Advanced Metering Infrastructure (AMI) network. Since the AMI network consists of thousands of smart meters, it is built as a wireless mesh network (WMN) because it requires far less cabling work, thereby lowering the infrastructure, deployment and maintenance costs. However, WMNs suffer from scalability issues as the network grows. Therefore, in this paper, we present a scalable protocol stack for the IEEE 802.11s-based AMI applications. We propose several modifications and parameter adjustments at different layers of the protocol stack. Specifically, several parameters at the MAC layer are adjusted. Furthermore, we integrate a modified Address Resolution Protocol to take advantage of Hybrid Wireless Mesh Protocol's proactive route requests/replies, which is IEEE 802.11s standards default routing protocol. Moreover, we propose five novel retransmission timeout (RTO) calculation functions for the application layer protocol, CoAP, in order to increase the reliability. We assessed the performance of the proposed protocol stack under the widely used ns-3 simulator. The simulation results have shown that the proposed stack can reliably scale to thousands of nodes.

Access control is an important component in the security of communication systems. While cryptography has rightfully been a significant component in the design of large scale communication systems, its relation to access control, especially its complementarity, has not often been brought out in full. With the wide availability of SELinux, a comprehensive model of access control has all the more become important. In many large scale systems, access control and trust management have become important components in the design. In survivable systems, models of group communication systems may have to be integrated with access control models. In this paper, we discuss the problem of integrating various formalisms often encountered in large scale communication systems, especially in connection with dynamic access control policies as well as trust management.

This paper establishes a smart meter reading solution with Long Rang (Lo Ra) as the regional dedicated communication network to provide a communication guarantee for automatic meter reading in multiple application scenarios. First, the paper analyzes the key performance indicators of LoRa technology. Based on the analysis of system performance and function, combined with the requirements of the power industry and application scenarios, the architecture design, and hardware and software design scheme of smart meter reading system with LoRa are presented. On this basis, an optimization method of LoRa key performance indicators is proposed. Finally, after comparing the communication distance, communication energy consumption, and meter reading success rate, the superiority of the smart meter reading solution based on LoRa was confirmed.

Smart meters are key components of the smart grid infrastructure, connecting households to utility providers. With Internet connectivity to such devices, the smart grid Advanced Metering Infrastructure (AMI) is exposed to attacks by the adversary class. Any compromise of a smart meter may jeopardize the security of not just the household in question, but also the entire neighborhood network and possibly the utility provider's core network. One attack category that may pose a serious threat to the AMI is a meter compromise attack, wherein a smart meter is controlled by the adversary, with the intent of committing energy fraud. In this paper, we present a detection model based on a cumulative analysis of smart meter readings of clustered smart meters. The clustering of smart meters is done based on the physical deployment points of individual smart meters within a neighbourhood area network. Results obtained through simulation of the proposed scheme are promising.

With the substantial increase in implementation of green technology across all sectors worldwide to overcome energy loss, attributes such as reliability, efficiency, productivity, and security become very crucial for a system. Especially with the integration of IoT and smart features into a system alongside the evolution of Internet, cybersecurity and privacy of an individual component should be taken into important consideration. A smart grid comprises wireless network components exposed to cyber-attacks, smart meters being one the most vulnerable part of an advanced metering infrastructure. An advanced metering infrastructure enables two-way communication for automatic meter readings (AMR) and transmits data through wireless network. To counter cyber-attacks afflicting the network of AMI and functioning of a smart meter, additional intrusion detection methods are implemented into the grid network. The review includes cybersecurity concerns associated with smart meters along with an in-depth insight to some major cyber-attacks and their aftermath.KeywordsCybersecurityCyber-attacks advanced metering infrastructure (AMI)Smart metersDenial-of-service (DoS)False data injection (FDI)Man-in-the-middle (MitM)

© 2014 IEEE. Smart home, which controls the end use of the power grid, has become a critical component in the smart grid infrastructure. In a smart home system, the advanced metering infrastructure (AMI) is used to connect smart meters with the power system and the communication system of a smart grid. The electricity pricing information is transmitted from the utility to the local community, and then broadcast through wired or wireless networks to each smart meter within AMI. In this work, the vulnerability of the above process is assessed. Two closely related pricing cyberattacks which manipulate the guideline electricity prices received at smart meters are considered and they aim at reducing the expense of the cyberattacker and increasing the peak energy usage in the local community. A countermeasure technique which uses support vector regression and impact difference for detecting anomaly pricing is then proposed. These pricing cyberattacks explore the interdependance between the transmitted electricity pricing in the communication system and the energy load in the power system, which are the first such cyber-Attacks in the smart home context. Our simulation results demonstrate that the pricing cyberattack can reduce the attacker's bill by 34.3% at the cost of the increase of others' bill by 7.9% on average. In addition, the pricing cyberattack can unbalance the energy load of the local power system as it increases the peak to average ratio by 35.7%. Furthermore, our simulation results show that the proposed countermeasure technique can effectively detect the electricity pricing manipulation.

Performance and Reliability Analysis of Computer Systems: An Example-Based Approach Using the SHARPE Software Package provides a variety of probabilistic, discrete-state models used to assess the reliability and performance of computer and communication systems. The models included are combinatorial reliability models (reliability block diagrams, fault trees and reliability graphs), directed, acyclic task precedence graphs, Markov and semi-Markov models (including Markov reward models), product-form queueing networks and generalized stochastic Petri nets. A practical approach to system modeling is followed; all of the examples described are solved and analyzed using the SHARPE tool. In structuring the book, the authors have been careful to provide the reader with a methodological approach to analytical modeling techniques. These techniques are not seen as alternatives but rather as an integral part of a single process of assessment which, by hierarchically combining results from different kinds of models, makes it possible to use state-space methods for those parts of a system that require them and non-state-space methods for the more well-behaved parts of the system. The SHARPE (Symbolic Hierarchical Automated Reliability and Performance Evaluator) package is the `toolchest' that allows the authors to specify stochastic models easily and solve them quickly, adopting model hierarchies and very efficient solution techniques. All the models described in the book are specified and solved using the SHARPE language; its syntax is described and the source code of almost all the examples discussed is provided. Audience: Suitable for use in advanced level courses covering reliability and performance of computer and communications systems and by researchers and practicing engineers whose work involves modeling of system performance and reliability.

The protection of smart meters (SMs) from cyberattacks is of utmost importance because SMs in advanced metering infrastructure (AMI) are physically unprotected and produce a large amount of sensitive data. Due to scalability, the SMs are small-sized and low-cost devices having low computational capabilities. The algorithms that are designed to complete the security requirements of SMs should be lightweight. To address this issue, this paper proposes a lightweight security solution to address the man-in-the-middle attack, data tempering, and blockchain-based data provenance. Received signal strength indicator (RSSI) is used to generate link fingerprints, which are used along with pseudo-random nonce to secure AMI. The proposed algorithm detects the involvement of adversarial node or meter tempering by computing other values along with 0 and 1 as the average of consecutive RSSI and difference between the RSSI of connected static SMs. Pearson correlation coefficient ( $\rho $ ) of 0.9102 is achieved when no adversarial node is present in between the connected SMs having mobility in one or both SMs. Negative or approximately equal to zero values of $\rho $ are computed when the adversary is present in the AMI or any of the SM in the AMI is forged. For blockchain-based data provenance, all the hash values of the packet header are 100% matched with the hash functions present at the data concentrator unit (DCU), which shows no adversary’s involvement in AMI. For cases when the adversary is in the AMI, hash functions show no match with the hash values present at the DCU.

Advanced Metering Infrastructure (AMI) enables two-way communication between smart devices and utility control centers. This involves remote monitoring and control of energy consumption as well as other parameters in the electrical power network in real time. However, increasing technologies in AMI due to huge deployment of smart meters, integration of devices and application of sensors, demand a strong architectural model with the best network topology to guarantee efficient usage of network resources with minimal latency. In this work, a resource efficient multi-hop network architecture is proposed using hybrid media access protocols. The architecture combines queuing and random-access protocol to achieve optimal network performance. Numerical results show that the probability of delay incurred by an arbitrary smart meter depends on the mean and distribution of the queue switch over a period. It is also observed that for a single queued system, the throughput performance is equal to the existing hybrid method. As the number of smart meters increases to 500, the throughput of the proposed method improves by 10% compared to the existing method. Likewise, as the number of smart meters increases to 500, the delay reduced by 15% compared to the existing method. Keywords: Advanced Metering Infrastructure; hybrid media access protocols; Smart Meter; Smart Grid; Power Network.

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.

The advanced metering infrastructure (AMI) is a crucial component of the smart grid, replacing traditional analog devices with computerized smart meters. Smart meters have not only allowed for efficient management of many end-users, but also have made AMI an attractive target for remote exploits and local physical tampering with the end goal of stealing energy. While smart meters posses multiple sensors and data sources that can indicate energy theft, in practice, the individual methods exhibit many false positives. In this paper, we present AMIDS, an AMI intrusion detection system that uses information fusion to combine the sensors and consumption data from a smart meter to more accurately detect energy theft. AMIDS combines meter audit logs of physical and cyber events with consumption data to more accurately model and detect theft-related behavior. Our experimental results on normal and anomalous load profiles show that AMIDS can identify energy theft efforts with high accuracy. Furthermore, AMIDS correctly identified legitimate load profile changes that more elementary analyses classified as malicious.

In this paper, we propose a unified approach for compression and authentication of smart meter reading in advanced metering infrastructure (AMI). In general, smart meters are urged to send sampled reading signals at a high rate for high-quality services. Meanwhile, power reading signals have to be authenticated to prevent impersonation attacks, which can cause serious economic loss. However, the security in smart grids faces more challenges than conventional human-type communications because of limited hardware resources of a smart meter (e.g., small memory). Motivated by these problems, we study simultaneous compression and authentication for power reading signals in multicarrier systems based on the notion of compressive sensing (CS). The CS-based compression and authentication method are applied to empirically modeled signals with a shared secret key, a measurement matrix in CS between a data concentrator unit (DCU) and a legitimate smart meter. In particular, for authentication, the residual error of a received signal at the DCU is used as a test statistic for hypothesis testing, which determines whether the signal is a legitimate signal or an intrusion signal in the proposed approach. Through the analysis and simulation results, we demonstrate that the CS-based compression approach can be applied to smart meter reading with good energy efficiency. In addition, it is shown that the proposed scheme can obtain a low authentication error probability under reasonable conditions. For example, when the number of subcarriers is 64, the DCU can distinguish legitimate and intrusion smart meters with a probability of $1 - P_{E}$ , where $P_{E} \leq 10^{-4}$ .

The literature does not present integral solutions to allow using the same credential to access the smart meter and smart house from an electric utility and vice-versa. The main reason being the technology gap in the communication between the Advanced Metering Infrastructure (AMI) and the Internet. The technology used in the Internet domain to communicate with Data Concentrators (DC) and the electric utility is more powerful than the technology used in the communication between smart meters and the DC, which is bandwidth limited and better suited to the Internet of Things (IoT) domain. Therefore, we are proposing the use of Identity Management (IdM) and a key-based scheme to enable the integration of IoT and the Internet using the same credentials, without creating a security bottleneck in the communication. An additional security mechanism is provided in the smart house context to isolate the house from direct accesses from the Internet, though allowing the utility to reconfigure the electric power consumption profile to avoid a potential blackout, for instance. Our proposal includes multi-sensor anti-tampering techniques to provide physical protection to a smart meter, in conjunction with a multilevel integrity mechanism to provide logical protection to its resource-constrained microcontroller, given the smart meter is a key component to mitigate electricity consumption fraud. The prototype has shown that our proposal is feasible for protecting the smart house, smart meter and the end-to-end communication between smart meter or house and the utility.

With the rapid growth in cellular user quantity and quality of service demand, the resource allocation in device-to-device communication system significantly affects the overall efficiency and user experience. In this study, the resource allocation for large-scale device-to-device communication system is modelled as a constrained optimization problem with thousands of dimensionalities. Then, the variable-coupling relationship of the developed model is analysed and the mathematical proof is firstly provided, and a novel algorithm namely multi-modal mutation cooperatively coevolving particle swarm optimization is developed to optimize the ultra-high dimensional model. Finally, efficacy of the developed method is verified by a comprehensive set of case studies, some famous algorithms for the specialized literature are also employed for comparison. Experimental results shown that the developed algorithm can obtain accurate and robust optimization performance for different system scales. In addition, when the system scale increases to 1000 cellular users and 300 D2D-pair users, the developed method can still outperform the compared algorithms and output accurate resource allocation solution.