AMI Network Research Articles

P234 IT IS TIME THAT ITALIAN AMI NETWORKS ARE BASED ON DIAGNOSTIC–THERAPEUTIC PATHWAYS INCLUDING BOTH TYPES OF ACS (STEMI AND NSTEMI)

Abstract Background Nowadays AMI management represents one of the most challenging clinical scenarios. On 8 july 2022 ANMCO held a special event about the last 20 years of AMI networks in Italy. During this event it was highlighted how these networks – supported by ANMCO – led to mortality reduction in the last 20 years (till –57%). By the way, the networks are usually based on diagnostic–therapeutic (D–T) pathways that not include NSTEMI–ACS. At contrary, the prevalence of NSTEMI–ACS is increasing and it significantly contributes to whole mortality due to coronary heart disease in the world. Materials and Methods The Functional Cardiology Department of Marche Region (Italy) covers the territory of three provinces. This department provided a new diagnostic–therapeutic pathway for AMI–network on July 2022. Globally, the department provides heart diseases management to 500.000 subjects living in that area. Working group who proposed the new D–T pathway included: 1) all Cardiology Units Directors; 2) all Emergency System Directors; 3) all Emergency Rooms Directors. The diagnostic–therapeutic pathway was based on 1) latest ESC guidelines and whole medical licterature on the topic; 2) geographic area features; 3) logistic local criticisms; 4) multiple sharing meetings results. Results The D–T pathway was divided in two chapters: 1) STEMI–ACS; 2) NSTEMI–ACS. STEMI–ACS chapter included 7 steps: 1) Symptoms onset and Emergency System Alert; 2) out of hospital intervention; 3) emergency room (ER) intervention; 4) primary PCI; 5) in–hospital complications; 6) whole in–hospital management and back transfer to the spoke; 7) cardiac rehabilitation and secondary prevention programs. The novelties were represented by: 1) ECG trasmission to the ICUs; 2) detailed establishment of which HUB every town/city of the area is assigned to; 3) inclusion of cardiac rehabilitation and secondary prevention programs in the pathway; 4) inclusion of NSTEMI–ACS with the two revascularization arms cited by the ESC guidelines. Conclusions The reported D–T pathway appears very innovative in order to including both two types of ACSs (STEMI and NSTEMI). Considering the latest guidelines, it could be appropriate that new D–T pathways, promoted by AMI networks in Italy, include a specific chapter dedicated to NSTEMI–ACS, given that also this type of ACS may require a time–dependent revascularization therapy and the correct approach may affect mortality and the whole prognosis.

P67 MYOCARDIAL INFARCTION IN COVID AND NON–COVID PATIENTS: DIFFERENT TWINS

Abstract For about 2 months (from 13 January to 15 March 2022) our CICU–Cardiology department (spoke for the AMI network) of the "San Giovanni di Dio" Hospital of Frattamaggiore (Napoli) has assumed the role of Covid–CICU for ASL Napoli 2 Nord. We analyzed the data regarding patients hospitalized for acute myocardial infarction in our department from January to August, selected on the basis of the presence of SARS–COV2 infection at admission, and we noted some substantial differences between the two populations, although in the small sample examined. 15 of the 44 patients hospitalized with Covid (34%) were discharged with a diagnosis of acute myocardial infarction, while among non–Covid patients 46.4% had acute myocardial infarction. The average age and days of hospitalization were higher in Covid patients (70 vs 67 years and 8.9 vs 6 days), and Covid patients with myocardial infarction and heart failure were 50% vs 24.7% of non–Covid patients. Diabetes was present in 31.5% of Covid patients and 15.7% in non–Covid. The number of STEMIs was higher in the Covids (53.3% vs 15.7% of the non–Covids), probably because being CICU–COVID we also accepted patients with STEMI who otherwise would have been hospitalized in the CICU HUB. Despite the difficulties in managing acute coronary syndromes in Covid patients, 60% of all Covid patients hospitalized for infarction underwent a haemodynamic study (73% in non–Covid patients) and primary PTCA was guaranteed for 87.5% of Covid patients with STEMI in a reasonable time in that context (< 9 hours from admission to hospital). However, in the face of this considerable organizational effort, the 6–month and intra–hospital mortality in Covid patients hospitalized for infarction was 31.5% and 12.5%, much higher than that of non–Covid patients (2.2% and 1.1% respectively ). The STEMi data from COVID patients is not comforting either: in fact, 25% of them died within 6 months and 12.5% in hospital, despite almost all of them were treated with primary PTCA, although not in the first 3 hours. But the mortality of the Covid patients in our department with a prevalent respiratory commitment is even higher than that of the Covid patients with AMI, reaching 40% at 6 months. In the light of our limited experience, we can hypothesize that the therapeutic protocols used in heart attacks, despite the inevitable delays due to Covid and although they are not as effective as in non–Covid patients, nevertheless can have impact on the prognosis.

P225 CICU–COVID: SMALL NUMBERS BUT BIG DIFFERENCES

Abstract For about 2 months (from 13 January to 15 March 2022) our CICU–Cardiology department (spoke for the AMI network) of the "San Giovanni di Dio" Hospital of Frattamaggiore (Naples) has assumed the role of CICU–COVID for Local Health Authority Napoli 2 Nord. We analyzed data regarding patients hospitalized in our department from January to August, selected on the basis of the presence of SARS–COV2 infection at admission, and we noted some substantial differences between the two populations, despite in the small sample examined. Patients hospitalized with Covid were, on average, of older age (73 vs 66.3 years old) and their hospitalization was on average longer (9 days vs 6.5), with differences both in the percentage of patients hospitalized for acute myocardial infarction (46.4 % in non–Covid patients vs 34% in Covid patients) and in the type of myocardial infarction: in fact, among the Covid patients who arrived at the ward with a heart attack diagnosis, STEMIs were more numerous (53.3% vs 15.7 of the non–Covid patients) . This may be due to the fact that in the period in which we have acted as Covid–CICU we have also accepted patients with STEMI who otherwise would have been hospitalized in the CICU HUB. Furthermore, the Covid patients were mostly affected by other chronic pathologies: in particular diabetes (40.8% of Covid patients and 18.4% of non–covid patients) and heart failure (54.5% in Covid patients vs 38, 9% in non–Covid). Finally, we examined the data regarding intra–hospital and 6–month mortality, and here too we found substantial differences: 16 of the 44 patients hospitalized with covid (36% of the total) died within 6 months of admission (18.1% in hospital ), while among non–covid patients 6–month mortality was 7% and intra–hospital mortality was 2%. In detail, the difference in mortality between the two groups of patients with myocardial infarction was even more marked, being the 6–month mortality 33.3% in Covid patients and 2.2% in non–Covid. Again, the group of Covid patients who died was affected by diabetes in a much higher percentage than the non–covid (56% vs 28.6%) These data come from a very small sample but nevertheless indicate that the simultaneous infection with SARS–COV2 dramatically worsens the prognosis of patients who normally refer to the CICU–Cardiology departments, and that some associated pathologies affect the prognosis even more significantly than others.

Intrusion detection framework based on homomorphic encryption in AMI network

In order to alleviate the privacy issue of traditional smart grids, some researchers have proposed a power metering system based on a federated learning framework, which jointly trains the model by exchanging gradients between multiple data owners instead of raw data. However, recent research shows that the federated learning framework still has privacy and security issues. Secondly, since the server does not have direct access to all parties data sets and training process, malicious attackers may conduct poisoning attacks. This is a new security threat in federated learning - poisoning attack. However, solving the two problems at the same time seems to be contradictory because privacy protection requires the inseparability of the training gradients of all parties, and security requires the server to be able to identify the poisoned client. To solve the above issues, this paper proposes an intrusion detection method based on federated learning client-side security in AMI networks, which uses CKKS to protect model parameters. In addition, to resist the poisoning attack in federated learning, the model trained by the data processing center and the model trained by each client are firstly calculated for the direction similarity, and the similarity value is scaled as the adaptive weight of the aggregation model. Then, the size of each client model update is normalized to be the same size as the data processing center model update. Finally, the normalized updates and adaptive weights are weighted averaged to form a global model update. The research results show that the method in this paper can effectively resist inference attacks and poisoning attacks. In the AMI network, the intrusion detection method based on federated learning can maintain a good detection performance.

Towards an Efficient Method for Large-Scale Wi-SUN-Enabled AMI Network Planning

In a smart grid communication network, positioning key devices (routers and gateways) is an NP-Hard problem as the number of candidate topologies grows exponentially according to the number of poles and smart meters. The different terrain profiles impose distinct communication losses between a smart meter and a key device position. Additionally, the communication topology must consider the position of previously installed distribution automation devices (DAs) to support the power grid remote operation. We introduce the heuristic method AIDA (AI-driven AMI network planning with DA-based information and a link-specific propagation model) to evaluate the connectivity condition between the meters and key devices. It also uses the link-received power calculated for the edges of a Minimum Spanning Tree to propose a simplified multihop analysis. The AIDA method proposes a balance between complexity and efficiency, eliminating the need for empirical terrain characterization. Using a spanning tree to characterize the connectivity topology between meters and routers, we suggest a heuristic approach capable of alleviating complexity and facilitating scalability. In our research, the interest is in proposing a method for positioning communication devices that presents a good trade-off between network coverage and the number of communication devices. The existing literature explores the theme by presenting different techniques for ideal device placement. Still rare are the references that meticulously explore real large-scale scenarios or the communication feasibility between meters and key devices, considering the detailed topography between the devices. The main contributions of this work include: (1) The presentation of an efficient AMI planning method with a large-scale focus; (2) The use of a propagation model that does not depend on an empirical terrain classification; and (3) The use of a heuristic approach based on a spanning tree, capable of evaluating a smaller number of connections and, even so, proposing a topology that uses fewer router and gateway positions compared to an approach that makes general terrain classification. Experiments in four real large-scale scenarios, totaling over 230,000 smart meters, demonstrate that AIDA can efficiently provide high-quality connectivity demanding a reduced number of devices. Additional experiments comparing AIDA's detailed terrain-based propagation model to the Erceg-SUI Path Loss model suggest that AIDA can reach the smart meter's coverage with a fewer router positions.

P353 THE “TIMES” IN COVID–TIME: EXPERIENCE OF A CICU “SPOKE”

Abstract We analyzed data regarding patients hospitalized in the period 03/09/2020–03/09/2021 in the ICU–Cardiology Division of the “San Giovanni di Dio Hospital” of Frattamaggiore (NA), configured as “Spoke” CICu for the AMI Network of the Campania Region, and we compared them with the same parameters of patients hospitalized during 2019. In particular, we analyzed differences in epidemiologic parameters and, in patients hospitalized for acute coronary syndromes, we evaluated the waiting times for hemodynamic procedures. The total number of hospitalized patients decreased by about 25%, while the mean age of patients and the percentage of hemodynamic procedures were comparable. In particular we noted that, while the percentages of patients hospitalized for acute myocardial infarction were similar in COVID and PRE–COVID era, during the pandemic in patients affected by acute myocardial infarction.the percentages of STEMIs were superior to those of NSTEMIs. Finally, we examined door–to–balloon times. In patients affected by STEMI we found that, even during the pandemic, primary angioplasty was performed on average within 100 minutes, meaning that ultra–fast swabs (mandatory before the procedure) did not produce delay. Moreover, in the pandemic period patients with NSTEMI, despite a stay of about 8 hours in ER to obtain the result of the antigenic swab for SARS–COV2, received coronary arteriography in a shorter time than in the pre–pandemic era (52,8 and 62,4 hours respectively). This analysis seems to show that the pandemic has not affected the access and hospitalization times of patients with acute coronary syndrome, and that, although greatest difficulties have arisen, the times of access to hemodynamics have not been affected by COVID.

Fed_ADBN: An efficient intrusion detection framework based on client selection in AMI network

AbstractData transmission between smart meters and data center is facing network security threats in advanced metering infrastructure of smart grid. The traditional solution is to move the data to the data center to build a centralized attack detection model, or divide the collected data into several independent and identically distributed datasets to build a distributed attack detection model. However, the long‐distance transmission and the centralized storage of data not only increase the communication overhead and time overhead, but also increase the risk of being attacked, causing privacy disclosure during the process of building the model. In this paper, we propose an efficient intrusion detection framework Fed_ADBN based on federated attention deep belief network and client selection. Clients cooperate with the data center to jointly build a horizontal federated learning framework. Under the premise of protecting data security by keeping data on the clients, we design a client selection algorithm based on client computing power, communication quality and security risks, which can improve the operating efficiency of federated learning. We also deploy a deep belief neural network with attention mechanism in each client to accurately detect possible network attacks in AMI network in real time. Experimental results show that compared with state‐of‐the‐art methods, the proposed framework can not only maintain good detection accuracy but also protect privacy.

Empowered Hybrid Parent Selection for Improving Network Lifetime, PDR, and Latency in Smart Grid

To support the constraints of smart meters—low power and memory—of AMI network, RPL is considered as the most suitable routing protocol to be implemented in practice. Network lifetime, PDR, and latency are the critical issues to be focused on and addressed. Generally, single parent selection scheme cannot satisfy all expected performance requirements of RPL based on AMI network due to tradeoff between workload balancing and transmission performance, PDR and latency. Moreover, the single parent also suffers from the package size and transmission range. Then, multiparent solution is proposed to overcome these demerits using multipath transmission strategy. Although the existing multiparent solutions, MELT and MAHP, overcome the issue of transmission performance, they present low network lifetime since multiparent solution consumes high energy in data transmission. In this paper, we propose an “empowered hybrid parent selection (EHPS)” that exploits the merits of multiparent solution and the single parent with cognitive radio technology in a hybridizing scheme. To split the data packet efficiently under multipath transmission strategy, a fuzzy AHP (FAHP) is adopted; therefore, EHPS balances the workload effectively and maximizes the network lifetime over long transmission range and large data size. Moreover, by exploiting cognitive radio, EHPS is flexible to the transmission range and data size since it achieves the highest transmission performance, highest PDR, and lowest latency among others, while maintaining high network lifetime.

A fault tolerant routing scheme for advanced metering infrastructure: an approach towards smart grid

The wireless sensor network is gaining significant attention because of its ubiquitous deployability nature. In general, the role of the wireless sensor network is remarkable in smart city applications for data sensing, collecting, and transmitting. Advanced metering infrastructure is an automatic system for the reading of electricity consumption by individual users. The reading of data from meters normally communicated over a wireless medium. Apart from collecting and sensing, routing is one of the major attributes in the AMI network. Successful communication is possible when the link and node are in the proper state. In this paper, we propose a fault-tolerant routing mechanism named Grid Topological Routing scheme to provide an efficient route in case of encountering a faulty path. The simulation shows better performance against the Routing Protocol for Low-Power and Lossy Networks and Ad-Hoc On-Demand Vector algorithm in terms of power consumption and packet delivery ratio. This model is explicitly designed for the smart grid in India.

Maximum artificial intelligence and complete reconstruct of population-based AMI care

Abstract Background After creating a behemoth hub and spoke AMI network that encompasses more than 100 million patients in 5 countries, we have begun to incorporate Artificial Intelligence (AI) algorithms into our telemedicine strategy with the goal of creating comprehensive, very early AMI diagnosis and physician-free triage. In doing so, we have replaced door-to-balloon times (d2b) with symptom-to-balloon times (s2b) as an immutable objective. Purpose To incorporate AI attributes for very early AMI detection, triage, and management. Methods We expanded our effective telemedicine strategy (100 million population; 877,178 telemedicine encounters; 55% overall mortality reduction; $291 million cost savings) with a logistic reset to impact s2b. To do this, we incorporated our Single Lead 1.0 (lead I) and Single Lead 2.0 (lead V2) technology for self-administered AMI detection with our physician-free STEMI diagnosis and triage AI algorithms. Single Lead algorithms and physician-free protocols were generated by utilizing Machine Learning from our mammoth annotated EKG repository. Results In addition to three logistic markers of efficiency Time-to-Telemedicine Diagnosis (TTD), Door-In-Door-Out (DIDO) and Transfer Times (TT); we are monitoring s2b. A gradual release of the algorithms and single lead is occurring at the telemedicine spokes. Detailed results will be available at the time of presentation. Conclusions Impacting s2b, the Achilles Heel of Primary PCI, may be achieved with the use of patient-administered AMI detection tools. Incorporation of these technologies into AI algorithms will add to telemedicine efficiencies for population-based AMI care. Funding Acknowledgement Type of funding source: None

Energy-efficient density-based Fuzzy C-means clustering in WSN for smart grids

ABSTRACT Wireless sensor networks (WSNs) are preferred for industrial applications due to the progressive increase of sensor electronics. One such use is the deployment of WSNs in Smart Grids. The periodic data from the Smart Meters and critical information are transferred by the AMI network between the customer site and MDMS through WSNs. The AMI is composed of various sensors for metering purposes. These sensors communicate with the base station in a restricted range. In this article, an energy-efficient routing for WSNs in AMI networks is proposed through density-based Fuzzy C-Means clustering (DFCM) to attain load balancing. The obtained simulation results show that DFCM can provide satisfactory performance and is suitable for data collection in Smart Grids.

AMI Network Failure Analysis based on Graph Database

최근 전국 각 지역 AMI(Advanced Metering Infrastructure) 원격검침 시스템의 보급사업이 활성화되고 있으 며, 전력수요 관리를 위한 양방향 통신 및 보안 요금제 기능 등 다양한 계량 기능을 제공하고 있다. 현재 AMI 시스템은 새로운 내부 IoT 장비 및 네트워크 규모의 증가로 인해 기존 RDB(Relational Database) 기반 장애 분석이 어렵다. 본 연구는 기존 RDB 데이터를 활용하는 새로운 GDB(Graph Database)기반 장애 분석 방법을 제안한다. 내부 임계치 와 상태 값 등 누적된 데이터를 통해 새로운 장애 패턴의 상관관계를 분석한다. GDB 기반 시뮬레이션 결과 RDB에서 분석이 어려웠던 새로운 장애 패턴을 예측할 수 있음을 확인하였다.

Lightweight and secure PUF-based authenticated key agreement scheme for smart grid

Smart Grid technology with the help of Information Technology (IT) adds many benefits to the traditional grids, but security concerns and especially privacy preserving of users is still a major practical issue. Establishing a secure and reliable communication channel between smart meters and service provider can guarantee data privacy in AMI network. This secure channel can be established with data encryption using a session key which is generated during an authentication scheme. This scheme should be enough lightweight to implement on resource constrained smart meters in delay sensitive AMI network. In this work, we analyze proposed PUF-based authenticated key agreement scheme by Gope et al. and show that their scheme is vulnerable in CK-adversary model and does not provide session key secrecy and backward secrecy. We propose an end-to-end PUF-based key agreement scheme between smart meters and service provider in AMI network which is secure against physical tampering attack and also it provides security in CK-Adversary model for ephemeral leakage attack. Our scheme imposes low communication and computational costs to smart meters. We analyze the security of our proposed scheme against popular attacks and verify its security by using widely accepted scyther tool.

P3352Telemedicine transcends national boundaries in quest of creating a behemoth ami program

Abstract Background The Latin America Telemedicine Infarct Network (LATIN) has exploited the remarkable competence of telemedicine for remote guidance. In doing so, LATIN created a mammoth population-based AMI network that employed experts located several hundred miles away to guide the reperfusion strategies for almost 800,000 screened patients. In this pioneering project, telemedicine was initially utilized to guide AMI management within national confines. We speculated whether LATIN telemedicine navigation could outstrip countrywide borders. Purpose To maximally harness the vast possibilities of telemedicine for improving AMI care. Methods During its pilot phase, LATIN began as a hub and spoke, AMI system in Colombia where 20 spokes (small community health centers and rural clinics) were configured with 3 hubs that could perform Primary PCI. These sites were linked through web-based connectivity. Expert cardiologists, located 50–250 miles away in Bogota, Colombia, used sophisticated telemedicine platforms for urgent EKG diagnosis and teleconsultation of the entire AMI process. Based upon the duration of chest pain and travel time to the hub, these experts guided patients through guideline-based strategies of thrombolysis, pharmaco invasive management or primary PCI. Efficiency of the telemedicine process was measured with the new metric of time to telemedicine diagnosis (TTD). Cloud computing, GPS navigation, and numerous business intelligent tools were gradually incorporated into LATIN telemedicine. As systems became more scalable, the program was expanded to Brazil, where LATIN flourished. Over the last 18 months, LATIN telemedicine capabilities have been pressed across national boundaries. Presently, all 82 LATIN centers in Mexico are guided by experts located in Bogota, Colombia and the 7 Argentina centers channeled through Santiago, Chile. Results 784,947 patients were screened for AMI at 350 LATIN centers (Brazil 143, Colombia 118, Mexico 82, Argentina 7). Navigation pathways are depicted in the attached figure. TTD remains extremely low in all four countries, and comparable efficiency and tele-accuracy have been achieved. With expanded geographic reach, 8,448 (1.08%) patients were diagnosed with STEMI and 3,911 (46.3%) urgently reperfused, including 3,049 (78%) with Primary PCI. Time to TTD ranged between 2.8 to 5.8 minutes, with a mean of 3.5 min. Tele-accuracy was 98.5%, D2B 51 min, and in-hospital mortality 5.2%. Various other comparative metrics for the 4 countries are being gathered and will be available at the time of presentation. Conclusions LATIN demonstrates the robust ability of telemedicine to transcend national boundaries to guide AMI management. This strategy can be adopted in under-developed countries in Asia and Africa to provide an umbrella of AMI care for the millions of disadvantaged patients.

Overview of Data Aggregation Schemes in a Smart Grid AMI Network

Overview of Data Aggregation Schemes in a Smart Grid AMI Network

Security issues in AMI network

Smart Grid is now the need of homes utilities and the customers because digitization of the grid system provides significant benefits like rich information at lower cost greener energy increased efficiency etc Metering infrastructure plays an important role in the smart grid and acts as an important interface between utilities and its consumers A metering network comprises a large number of different types of energy meters like advanced meters and legacy meters To achieve the vision of smart grid above said metering networks are integrated for exchanging the usage data and taking necessary control actions Therefore making grid digitization introduces lot of concerns about their security To understand various security issues this article discusses plurality of threats involved at different stages in the AMI system

SMAC: A Soft MAC to Reduce Control Overhead and Latency in CDMA-Based AMI Networks

The use of state-of-the-art 3G cellular CDMA technologies in a utility owned AMI network results in a large amount of control traffic relative to data traffic, increases the average packet delay and hence are not an appropriate choice for smart grid distribution applications. Like the CDG, we consider a utility owned cellular like CDMA network for smart grid distribution applications and classify the distribution smart grid data as scheduled data and random data. Also, we propose SMAC protocol, which changes its mode of operation based on the type of the data being collected to reduce the data collection latency and control overhead when compared to 3G cellular CDMA2000 MAC. The reduction in the data collection latency and control overhead aids in increasing the number of smart meters served by a base station within the periodic data collection interval, which further reduces the number of base stations needed by a utility or reduces the bandwidth needed to collect data from all the smart meters. The reduction in the number of base stations and/or the reduction in the data transmission bandwidth reduces the CAPital EXpenditure (CAPEX) and OPerational EXpenditure (OPEX) of the AMI network. The proposed SMAC protocol is analyzed using markov chain, analytical expressions for average throughput and average packet delay are derived, and simulation results are also provided to verify the analysis.

Efficient topology construction and routing for IEEE 802.15.4m-based smart grid networks

IEEE 802.15.4m TVWS Multi-Channel Tree PAN (TMCTP) standard that uses the vacant TV frequency of a region is the key to provide a flexible, scalable and cost-effective AMI smart grid networks. However, the performance of the IEEE 802.15.4m based AMI network can suffer from network interruption, varying transmission reliability and energy consumption problems due to the excessive number of channels and periodic channel scanning. To resolve these issues, we presented an enhanced IEEE 802.15.4m TMCTP called TVWS Orphan channel scanning with Multi-Channel Tree PAN Routing (TOMTPR). The proposed TOMTPR framework includes pilot-channel based Multi-Channel beaconing and interleaving-based TVWS orphan channel scanning. Furthermore, a capacity-aware routing tree is constructed during the neighbor discovery procedure. The proposed protocol suite is designed to provide compatibility with the IEEE 802.15.4 family standards with lower architecture complexity. The simulation results in presence of realistic AMI traffic and AMI network model show that TOMTPR can not only satisfy delay requirements of the AMI traffic, but also outperforms IEEE 802.15.4m TMCTP with IEEE 802.15.5 layer 2 mesh routing in terms of topology construction delay, end-to-end transmission reliability, and energy efficiency.

Diseño y evaluación del desempeño de una red de comunicaciones para medición inteligente en Network Simulator–2

<p>Este artículo presenta los resultados de diseño y evaluación del desempeño de una red de comunicaciones para Medición Inteligente o AMI (<em>Advanced Metering Infrastructure</em>), empleando el simulador de redes <em>Network Simulator</em>-2 (NS-2). La red de comunicaciones propuesta combina las tecnologías PLC (<em>PowerLine Communication</em>) y HSDPA (<em>High Speed Downlin Packet Access</em>), así como el uso de concentradores de datos (DCs) y de protocolos aplicación y transporte como DLMS/COSEM y TCP-UDP/IP. Los resultados de evaluación indicaron que al introducir dispositivos DCs dentro del diseño de red de comunicaciones, la red presenta un desempeño superior frente a otras que no emplean DCs para concentrar la información de diferentes medidores inteligentes. Finalmente, se observó una mayor cobertura y un menor número de acceso directos a la red de comunicaciones al considerar DCs en el diseño.</p>

Enhanced ID-Based Authentication Scheme Using OTP in Smart Grid AMI Environment

This paper presents the vulnerabilities analyses of KL scheme which is an ID-based authentication scheme for AMI network attached SCADA in smart grid and proposes a security-enhanced authentication scheme which satisfies forward secrecy as well as security requirements introduced in KL scheme and also other existing schemes. The proposed scheme uses MDMS which is the supervising system located in an electrical company as a time-synchronizing server in order to synchronize smart devices at home and conducts authentication between smart meter and smart devices using a new secret value generated by an OTP generator every session. The proposed scheme has forward secrecy, so it increases overall security, but its communication and computation overhead reduce its performance slightly, comparing the existing schemes. Nonetheless, hardware specification and communication bandwidth of smart devices will have better conditions continuously, so the proposed scheme would be a good choice for secure AMI environment.