An Optimal Medium Access Control with Partial Observations for Sensor Networks

We consider medium access control (MAC) in multihop sensor networks, where only partial information about the shared medium is available to the transmitter. We model our setting as a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain representing the available bandwidth, and in which the arrivals are controlled based on the partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state on which the control decisions are based. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results can be specifically applied for designing efficient and stable algorithms for medium access control in multiple-accessed systems, in particular for sensor networks

Traffic classification and prediction, and fast uplink grant allocation for machine type communications via support vector machines and long short-term memory

Abstract. The current random access (RA) allocation techniques suffer from congestion and high signaling overhead while serving machine type communication (MTC) applications. Therefore, 3GPP has introduced the need to use fast uplink grant (FUG) allocation. This thesis proposes a novel FUG allocation based on support vector machine (SVM) and long short-term memory (LSTM). First, MTC devices are prioritized using SVM classifier. Second, LSTM architecture is used to predict activation time of each device. Both results are used to achieve an efficient resource scheduler in terms of the average latency and total throughput. Furthermore, a set of correction techniques is introduced to overcome the classification and prediction errors. The Coupled Markov Modulated Poisson Process (CMMPP) traffic model is applied to compare the proposed FUG allocation to other existing allocation techniques. In addition, an extended traffic model based CMMPP is used to evaluate the proposed algorithm in a more dense network. Our simulation results show the proposed model outperforms the existing RA allocation schemes by achieving the highest throughput and the lowest access delay when serving the target massive and critical MTC applications

Design and Analysis of a Novel Split and Aggregated Transmission Control Protocol for Smart Metering Infrastructure

Utility companies (electricity, gas, and water suppliers), governments, and researchers recognize an urgent need to deploy communication-based systems to automate data collection from smart meters and sensors, known as Smart Metering Infrastructure (SMI) or Automatic Meter Reading (AMR). A smart metering system is envisaged to bring tremendous benefits to customers, utilities, and governments. The advantages include reducing peak demand for energy, supporting the time-of-use concept for billing, enabling customers to make informed decisions, and performing effective load management, to name a few. A key element in an SMI is communications between meters and utility servers. However, the mass deployment of metering devices in the grid calls for studying the scalability of communication protocols. SMI is characterized by the deployment of a large number of small Internet Protocol (IP) devices sending small packets at a low rate to a central server. Although the individual devices generate data at a low rate, the collective traffic produced is significant and is disruptive to network communication functionality. This research work focuses on the scalability of the transport layer functionalities. The TCP congestion control mechanism, in particular, would be ineffective for the traffic of smart meters because a large volume of data comes from a large number of individual sources. This situation makes the TCP congestion control mechanism unable to lower the transmission rate even when congestion occurs. The consequences are a high loss rate for metered data and degraded throughput for competing traffic in the smart metering network. To enhance the performance of TCP in a smart metering infrastructure (SMI), we introduce a novel TCP-based scheme, called Split- and Aggregated-TCP (SA-TCP). This scheme is based on the idea of upgrading intermediate devices in SMI (known in the industry as regional collectors) to offer the service of aggregating the TCP connections. An SA-TCP aggregator collects data packets from the smart meters of its region over separate TCP connections; then it reliably forwards the data over another TCP connection to the utility server. The proposed split and aggregated scheme provides a better response to traffic conditions and, most importantly, makes the TCP congestion control and flow control mechanisms effective. Supported by extensive ns-2 simulations, we show the effectiveness of the SA-TCP approach to mitigating the problems in terms of the throughput and packet loss rate performance metrics. A full mathematical model of SA-TCP is provided. The model is highly accurate and flexible in predicting the behaviour of the two stages, separately and combined, of the SA-TCP scheme in terms of throughput, packet loss rate and end-to-end delay. Considering the two stages of the scheme, the modelling approach uses Markovian models to represent smart meters in the first stage and SA-TCP aggregators in the second. Then, the approach studies the interaction of smart meters and SA-TCP aggregators with the network by means of standard queuing models. The ns-2 simulations validate the math model results. A comprehensive performance analysis of the SA-TCP scheme is performed. It studies the impact of varying various parameters on the scheme, including the impact of network link capacity, buffering capacity of those RCs that act as SA-TCP aggregators, propagation delay between the meters and the utility server, and finally, the number of SA-TCP aggregators. The performance results show that adjusting those parameters makes it possible to further enhance congestion control in SMI. Therefore, this thesis also formulates an optimization model to achieve better TCP performance and ensures satisfactory performance results, such as a minimal loss rate and acceptable end-to-end delay. The optimization model also considers minimizing the SA-TCP scheme deployment cost by balancing the number of SA-TCP aggregators and the link bandwidth, while still satisfying performance requirements

Design and Analysis of a Novel Split and Aggregated Transmission Control Protocol for Smart Metering Infrastructure

Utility companies (electricity, gas, and water suppliers), governments, and researchers recognize an urgent need to deploy communication-based systems to automate data collection from smart meters and sensors, known as Smart Metering Infrastructure (SMI) or Automatic Meter Reading (AMR). A smart metering system is envisaged to bring tremendous benefits to customers, utilities, and governments. The advantages include reducing peak demand for energy, supporting the time-of-use concept for billing, enabling customers to make informed decisions, and performing effective load management, to name a few. A key element in an SMI is communications between meters and utility servers. However, the mass deployment of metering devices in the grid calls for studying the scalability of communication protocols. SMI is characterized by the deployment of a large number of small Internet Protocol (IP) devices sending small packets at a low rate to a central server. Although the individual devices generate data at a low rate, the collective traffic produced is significant and is disruptive to network communication functionality. This research work focuses on the scalability of the transport layer functionalities. The TCP congestion control mechanism, in particular, would be ineffective for the traffic of smart meters because a large volume of data comes from a large number of individual sources. This situation makes the TCP congestion control mechanism unable to lower the transmission rate even when congestion occurs. The consequences are a high loss rate for metered data and degraded throughput for competing traffic in the smart metering network. To enhance the performance of TCP in a smart metering infrastructure (SMI), we introduce a novel TCP-based scheme, called Split- and Aggregated-TCP (SA-TCP). This scheme is based on the idea of upgrading intermediate devices in SMI (known in the industry as regional collectors) to offer the service of aggregating the TCP connections. An SA-TCP aggregator collects data packets from the smart meters of its region over separate TCP connections; then it reliably forwards the data over another TCP connection to the utility server. The proposed split and aggregated scheme provides a better response to traffic conditions and, most importantly, makes the TCP congestion control and flow control mechanisms effective. Supported by extensive ns-2 simulations, we show the effectiveness of the SA-TCP approach to mitigating the problems in terms of the throughput and packet loss rate performance metrics. A full mathematical model of SA-TCP is provided. The model is highly accurate and flexible in predicting the behaviour of the two stages, separately and combined, of the SA-TCP scheme in terms of throughput, packet loss rate and end-to-end delay. Considering the two stages of the scheme, the modelling approach uses Markovian models to represent smart meters in the first stage and SA-TCP aggregators in the second. Then, the approach studies the interaction of smart meters and SA-TCP aggregators with the network by means of standard queuing models. The ns-2 simulations validate the math model results. A comprehensive performance analysis of the SA-TCP scheme is performed. It studies the impact of varying various parameters on the scheme, including the impact of network link capacity, buffering capacity of those RCs that act as SA-TCP aggregators, propagation delay between the meters and the utility server, and finally, the number of SA-TCP aggregators. The performance results show that adjusting those parameters makes it possible to further enhance congestion control in SMI. Therefore, this thesis also formulates an optimization model to achieve better TCP performance and ensures satisfactory performance results, such as a minimal loss rate and acceptable end-to-end delay. The optimization model also considers minimizing the SA-TCP scheme deployment cost by balancing the number of SA-TCP aggregators and the link bandwidth, while still satisfying performance requirements

Token Bucket Algorithm with Modernization Techniques to Avoid Congestion in DEC Protocol of Wsn

A wireless sensor system is an essential aspect in many fields. It consists of a great deal of sensor nodes. These sensor networks carry out a number of tasks, including interaction, distribution, recognition, and power supply. Data is transmitted from source to destination and plays an important role. Congestion may occur during data transmission from one node to another and also at cluster head locations. Congestion will arise as a result of either traffic division or resource allocation. Energy will be wasted due to traffic division congestion, which causes packet loss and retransmission of removed packets. As a result, it must be simplified; hence there are a few Wireless sensor networks with various protocols that will handle Congestion Control. The Deterministic Energy Efficient Clustering (DEC) protocol, which is fully based on residual energy and the token bucket method, is being investigated as a way to increase the energy efficiency. In the event of congestion, our proposal provides a way to cope with it and solves it using this method to improve lifespan of the sensor networks. Experiments in simulation show that the proposed strategy can significantly enhance lifetime, energy, throughput, and packet loss

Models of leader elections and their applications

New research about cyber-physical systems is rapidly changing the way we think about critical infrastructures such as the power grid. Changing requirements for the generation, storage, and availability of power are all driving the development of the smart-grid. Many smart-grid projects disperse power generation across a wide area and control devices with a distributed system. However, in a distributed system, the state of processes is hard to determine due to isolation of memory. By using information flow security models, we reason about a process\u27s beliefs of the system state in a distributed system. Information flow analysis aided in the creation of Markov models for the expected behavior of a cyber controller in a smart-grid system using a communication network with omission faults. The models were used as part of an analysis of the distributed system behavior when there are communication faults. With insight gained from these models, existing congestion management techniques were extended to create a feedback mechanism, allowing the cyber-physical system to better react to issues in the communication network --Abstract, page iii

A Survey on Dynamic Spectrum Access Techniques in Cognitive Radio Networks

The idea of Cognitive Radio (CR) is to share the spectrum between a user called primary, and a user called secondary. Dynamic Spectrum Access (DSA) is a new spectrum sharing paradigm in cognitive radio that allows secondary users to access the abundant spectrum holes in the licensed spectrum bands. DSA is an auspicious technology to alleviate the spectrum scarcity problem and increase spectrum utilization. While DSA has attracted many research efforts recently, in this paper, a survey of spectrum access techniques using cooperation and competition to solve the problem of spectrum allocation in cognitive radio networks is presented