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Alan Winfield - One of the best experts on this subject based on the ideXlab platform.
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special issue on swarm robotics
Swarm Intelligence, 2008Co-Authors: Erol şahin, Alan WinfieldAbstract:Swarm robotics is a new approach to the coordination of multi-robot systems. In contrast with traditional multi-robot systems which use centralised or hierarchical control and communication systems in order to coordinate robots’ behaviours, swarm robotics adopts a decentralised approach in which the desired collective behaviours emerge from the local interactions between robots and their environment. Such emergent or self-organised collective behaviours are inspired by, and in some cases Modelled on, the swarm intelligence observed in social insects. The potential for swarm robotics is considerable. Any task in which physically distributed objects need to be explored, surveyed, collected, harvested, rescued, or assembled into structures is a potential real-world application for swarm robotics. The key advantage of the swarm robotics approach is robustness, which manifests itself in a number of ways. Firstly, because a swarm of robots consists of a number of relatively simple and typically homogeneous robots, which are not pre-assigned to specific roles or tasks within the swarm, then the swarm can self-organise or dynamically re-organise the way individual robots are deployed. Secondly, and for the same reasons, the swarm approach is highly tolerant to the Failure of individual robots. Thirdly, the fact that control is completely decentralised means that there is no Common-Mode Failure point or vulnerability in the swarm. Indeed, it could be said that the high level of robustness evident in robotic swarms comes for free in the sense that it is intrinsic to the swarm robotics approach, which contrasts with the high engineering cost of fault tolerance in conventional robotic systems. The realisation of the potential of swarm robotics requires the solution of a number of very challenging problems. Firstly, in algorithm design: swarm roboticists face the problem of designing both the physical morphology and behaviours of the individual robots such that when those robots interact with each other and their environment, the desired overall collective behaviours will emerge. At present there are no principled approaches to the design of low-level behaviours for a given desired collective behaviour. Secondly, in implementation
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Special issue on swarm robotics
Swarm Intelligence, 2008Co-Authors: Erol şahin, Alan WinfieldAbstract:Swarm robotics is a new approach to the coordination of multi-robot systems. In contrast with traditional multi-robot systems which use centralised or hierarchical control and com-munication systems in order to coordinate robots' behaviours, swarm robotics adopts a de-centralised approach in which the desired collective behaviours emerge from the local in-teractions between robots and their environment. Such emergent or self-organised collective behaviours are inspired by, and in some cases Modelled on, the swarm intelligence observed in social insects. The potential for swarm robotics is considerable. Any task in which physically distrib-uted objects need to be explored, surveyed, collected, harvested, rescued, or assembled into structures is a potential real-world application for swarm robotics. The key advantage of the swarm robotics approach is robustness, which manifests itself in a number of ways. Firstly, because a swarm of robots consists of a number of relatively simple and typically homoge-neous robots, which are not pre-assigned to specific roles or tasks within the swarm, then the swarm can self-organise or dynamically re-organise the way individual robots are deployed. Secondly, and for the same reasons, the swarm approach is highly tolerant to the Failure of individual robots. Thirdly, the fact that control is completely decentralised means that there is no Common-Mode Failure point or vulnerability in the swarm. Indeed, it could be said that the high level of robustness evident in robotic swarms comes for free in the sense that it is intrinsic to the swarm robotics approach, which contrasts with the high engineering cost of fault tolerance in conventional robotic systems. The realisation of the potential of swarm robotics requires the solution of a number of very challenging problems. Firstly, in algorithm design: swarm roboticists face the problem of designing both the physical morphology and behaviours of the individual robots such that when those robots interact with each other and their environment, the desired overall collec-tive behaviours will emerge. At present there are no principled approaches to the design of low-level behaviours for a given desired collective behaviour. Secondly, in implementation Swarm Intell (2008) 2: 69–72 and test: to build and rigorously test a swarm of robots in the laboratory requires a con-siderable experimental infrastructure. Real-robot experiments thus typically proceed hand-in-hand with simulation and good tools are essential. Thirdly, in analysis and Modelling: a robotic swarm is typically a stochastic, non-linear system and constructing mathematical Models for both validation and parameter optimisation is challenging. Such Models would surely be an essential part of constructing a safety argument for real-world applications. There are, at the time of writing, no known real-world applications of swarm robotics and, given the challenges outlined above, this is perhaps not surprising. However, as the papers of this special issue demonstrate, the field of swarm robotics is developing very strongly, and we predict that real-world applications of swarm robotic systems will emerge in the near future. A total of seventeen papers were submitted to this special issue and, following a rigorous process of anonymous review, eight have been selected for publication. The papers included in this special issue cover a broad spectrum of the challenges outlined above, from Design and Algorithms including self-assembly, self-organised flocking, self-organised distribution, evolutionary robotics and – with an applications focus – swarming of Micro Air Vehicles for communications relay. One paper focuses on a new generation of simulation tool, and two papers on new approaches to mathematical Modelling and analysis. Outlined below, the eight papers of this special issue strongly represent the state-of-the-art in this vibrant field of research. Design and algorithms
Erol şahin - One of the best experts on this subject based on the ideXlab platform.
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special issue on swarm robotics
Swarm Intelligence, 2008Co-Authors: Erol şahin, Alan WinfieldAbstract:Swarm robotics is a new approach to the coordination of multi-robot systems. In contrast with traditional multi-robot systems which use centralised or hierarchical control and communication systems in order to coordinate robots’ behaviours, swarm robotics adopts a decentralised approach in which the desired collective behaviours emerge from the local interactions between robots and their environment. Such emergent or self-organised collective behaviours are inspired by, and in some cases Modelled on, the swarm intelligence observed in social insects. The potential for swarm robotics is considerable. Any task in which physically distributed objects need to be explored, surveyed, collected, harvested, rescued, or assembled into structures is a potential real-world application for swarm robotics. The key advantage of the swarm robotics approach is robustness, which manifests itself in a number of ways. Firstly, because a swarm of robots consists of a number of relatively simple and typically homogeneous robots, which are not pre-assigned to specific roles or tasks within the swarm, then the swarm can self-organise or dynamically re-organise the way individual robots are deployed. Secondly, and for the same reasons, the swarm approach is highly tolerant to the Failure of individual robots. Thirdly, the fact that control is completely decentralised means that there is no Common-Mode Failure point or vulnerability in the swarm. Indeed, it could be said that the high level of robustness evident in robotic swarms comes for free in the sense that it is intrinsic to the swarm robotics approach, which contrasts with the high engineering cost of fault tolerance in conventional robotic systems. The realisation of the potential of swarm robotics requires the solution of a number of very challenging problems. Firstly, in algorithm design: swarm roboticists face the problem of designing both the physical morphology and behaviours of the individual robots such that when those robots interact with each other and their environment, the desired overall collective behaviours will emerge. At present there are no principled approaches to the design of low-level behaviours for a given desired collective behaviour. Secondly, in implementation
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Special issue on swarm robotics
Swarm Intelligence, 2008Co-Authors: Erol şahin, Alan WinfieldAbstract:Swarm robotics is a new approach to the coordination of multi-robot systems. In contrast with traditional multi-robot systems which use centralised or hierarchical control and com-munication systems in order to coordinate robots' behaviours, swarm robotics adopts a de-centralised approach in which the desired collective behaviours emerge from the local in-teractions between robots and their environment. Such emergent or self-organised collective behaviours are inspired by, and in some cases Modelled on, the swarm intelligence observed in social insects. The potential for swarm robotics is considerable. Any task in which physically distrib-uted objects need to be explored, surveyed, collected, harvested, rescued, or assembled into structures is a potential real-world application for swarm robotics. The key advantage of the swarm robotics approach is robustness, which manifests itself in a number of ways. Firstly, because a swarm of robots consists of a number of relatively simple and typically homoge-neous robots, which are not pre-assigned to specific roles or tasks within the swarm, then the swarm can self-organise or dynamically re-organise the way individual robots are deployed. Secondly, and for the same reasons, the swarm approach is highly tolerant to the Failure of individual robots. Thirdly, the fact that control is completely decentralised means that there is no Common-Mode Failure point or vulnerability in the swarm. Indeed, it could be said that the high level of robustness evident in robotic swarms comes for free in the sense that it is intrinsic to the swarm robotics approach, which contrasts with the high engineering cost of fault tolerance in conventional robotic systems. The realisation of the potential of swarm robotics requires the solution of a number of very challenging problems. Firstly, in algorithm design: swarm roboticists face the problem of designing both the physical morphology and behaviours of the individual robots such that when those robots interact with each other and their environment, the desired overall collec-tive behaviours will emerge. At present there are no principled approaches to the design of low-level behaviours for a given desired collective behaviour. Secondly, in implementation Swarm Intell (2008) 2: 69–72 and test: to build and rigorously test a swarm of robots in the laboratory requires a con-siderable experimental infrastructure. Real-robot experiments thus typically proceed hand-in-hand with simulation and good tools are essential. Thirdly, in analysis and Modelling: a robotic swarm is typically a stochastic, non-linear system and constructing mathematical Models for both validation and parameter optimisation is challenging. Such Models would surely be an essential part of constructing a safety argument for real-world applications. There are, at the time of writing, no known real-world applications of swarm robotics and, given the challenges outlined above, this is perhaps not surprising. However, as the papers of this special issue demonstrate, the field of swarm robotics is developing very strongly, and we predict that real-world applications of swarm robotic systems will emerge in the near future. A total of seventeen papers were submitted to this special issue and, following a rigorous process of anonymous review, eight have been selected for publication. The papers included in this special issue cover a broad spectrum of the challenges outlined above, from Design and Algorithms including self-assembly, self-organised flocking, self-organised distribution, evolutionary robotics and – with an applications focus – swarming of Micro Air Vehicles for communications relay. One paper focuses on a new generation of simulation tool, and two papers on new approaches to mathematical Modelling and analysis. Outlined below, the eight papers of this special issue strongly represent the state-of-the-art in this vibrant field of research. Design and algorithms
Cheng Li - One of the best experts on this subject based on the ideXlab platform.
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overall voltage level reliability assessment of power system based on equivalent Model of substations
Power system technology, 2015Co-Authors: Cheng LiAbstract:In the past, the researches on reliability of distribution network usually regarded distribution system as an independent network, thus were lack of analyzing the relationship between the distribution network and substations, and that between the distribution network and the main network. Furthermore, the Common Mode outage of components was still underestimated. Therefore, on the basis of the operating characteristics of multi-level distribution network and considering the Common Mode Failure characteristics of disconnecting switches, the concept of Common Mode associated component and an extended minimal cut set algorithm were put forward. A substation equivalent Model was built, and a reliability evaluation algorithm of urban power grid was designed, on the basis of that, an overall reliability assessment method for power grid was proposed. Taking an actual grid as example, the weakness of case grid was analyzed and the results show that the evaluation index can reflect the power supply reliability level of actual users.
Yong Rae Kwon - One of the best experts on this subject based on the ideXlab platform.
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APSEC - Detecting Common Mode Failures in N-version software using weakest precondition analysis
Proceedings of Joint 4th International Computer Science Conference and 4th Asia Pacific Software Engineering Conference, 1997Co-Authors: Gwang Sik Yoon, Yong Rae KwonAbstract:An underlying assumption for N-version programming technique is that independently developed versions would fail in a statistically independent manner However empirical studies have demonstrated that Common Mode Failures can occur even for independently developed versions, and that Common Mode Failures degrade system reliability. In this paper, we demonstrate that the weakest precondition analysis is effective in determining input spaces leading to Common Mode Failures. We applied the weakest precondition to the Launch Interceptor Programs which were used in several other experiments related to the N-version programming technique. We detected 13 out of 18 fault pairs which have been known to cause Common Mode Failure. These faults were due to logical flaws in program design. Although the weakest precondition analysis may be labor-intensive since they are applied manually our results convincingly demonstrate that it is effective for identifying input spaces causing Common Mode Failures and further improving the reliability of N-version software.
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Detecting Common Mode Failures in N-version software using weakest precondition analysis
Proceedings of Joint 4th International Computer Science Conference and 4th Asia Pacific Software Engineering Conference, 1997Co-Authors: Gwang Sik Yoon, Yong Rae KwonAbstract:An underlying assumption for N-version programming technique is that independently developed versions would fail in a statistically independent manner However empirical studies have demonstrated that Common Mode Failures can occur even for independently developed versions, and that Common Mode Failures degrade system reliability. In this paper, we demonstrate that the weakest precondition analysis is effective in determining input spaces leading to Common Mode Failures. We applied the weakest precondition to the Launch Interceptor Programs which were used in several other experiments related to the N-version programming technique. We detected 13 out of 18 fault pairs which have been known to cause Common Mode Failure. These faults were due to logical flaws in program design. Although the weakest precondition analysis may be labor-intensive since they are applied manually our results convincingly demonstrate that it is effective for identifying input spaces causing Common Mode Failures and further improving the reliability of N-version software.
Benjamin Carrion Schafer - One of the best experts on this subject based on the ideXlab platform.
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ICCD - Learning-Based Diversity Estimation: Leveraging the Power of High-Level Synthesis to Mitigate Common-Mode Failure
2019 IEEE 37th International Conference on Computer Design (ICCD), 2019Co-Authors: Farah Naz Taher, Anjana Balachandran, Benjamin Carrion SchaferAbstract:Hardware redundancy techniques are extensively used for enhancing system reliability, availability and fault tolerance. However, traditional identical module N-modular redundancy (NMR) cannot protect against Common Mode Failures (CMFs). One method that has been proposed to protect against CMFs is the use of dissimilar (diverse) module redundancy. One of the problems with previous work is that it generates these diverse modules by perturbing the gate-netlist and thus, achieve very limited diversity. In addition, previous work is very time consuming as it requires to insert fault-pairs in the gate-netlists in order to measure the effect of these on the outputs. To address these issues, this work proposes to first increase diversity by raising the level of abstraction from the gate level to the behavioral level. Secondly, we propose a fast machine learning based method that facilitates the design space exploration (DSE) of single behavioral descriptions in order to generate optimized redundant hardware accelerator system with maximum diversity to protect against CMFs. For this purpose, this work exploits one of the main advantages of C-based VLSI design: The ability to generate micro-architectures with unique characteristics from the same behavioral description by setting different synthesis directives in the form of pragmas. Experimental results show that our proposed method is a fast and efficient way to generate diverse designs to protect the system against CMFs.
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Common-Mode Failure Mitigation: Increasing Diversity through High-Level Synthesis
2019 Design Automation & Test in Europe Conference & Exhibition (DATE), 2019Co-Authors: Farah Naz Taher, Matthew Joslin, Anjana Balachandran, Benjamin Carrion SchaferAbstract:Fault tolerance is vital in many domains. One popular way to increase fault-tolerance is through hardware redundancy. However, basic redundancy cannot cope with Common Mode Failures (CMFs). One way to address CMF is through the use of diversity in combination with traditional hardware redundancy. This work proposes an automatic design space exploration (DSE) method to generate optimized redundant hardware accelerators with maximum diversity to protect against CMFs given as a single behavioral description for High-Level Synthesis (HLS). For this purpose, this work exploits one of the main advantages of C-based VLSI design over the traditional RT-level design based on low-level Hardware Description Languages (HDLs): The ability to generate micro-architectures with unique characteristics from the same behavioral description. Experimental results show that the proposed method provides a significant diversity increment compared to using traditional RTL-based exploration to generate diverse designs.
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DATE - Common-Mode Failure Mitigation: Increasing Diversity through High-Level Synthesis
2019 Design Automation & Test in Europe Conference & Exhibition (DATE), 2019Co-Authors: Farah Naz Taher, Matthew Joslin, Anjana Balachandran, Benjamin Carrion SchaferAbstract:Fault tolerance is vital in many domains. One popular way to increase fault-tolerance is through hardware redundancy. However, basic redundancy cannot cope with Common Mode Failures (CMFs). One way to address CMF is through the use of diversity in combination with traditional hardware redundancy. This work proposes an automatic design space exploration (DSE) method to generate optimized redundant hardware accelerators with maximum diversity to protect against CMFs given as a single behavioral description for High-Level Synthesis (HLS). For this purpose, this work exploits one of the main advantages of C-based VLSI design over the traditional RT-level design based on low-level Hardware Description Languages (HDLs): The ability to generate micro-architectures with unique characteristics from the same behavioral description. Experimental results show that the proposed method provides a significant diversity increment compared to using traditional RTL-based exploration to generate diverse designs.
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Learning-Based Diversity Estimation: Leveraging the Power of High-Level Synthesis to Mitigate Common-Mode Failure
2019 IEEE 37th International Conference on Computer Design (ICCD), 2019Co-Authors: Farah Naz Taher, Anjana Balachandran, Benjamin Carrion SchaferAbstract:Hardware redundancy techniques are extensively used for enhancing system reliability, availability and fault tolerance. However, traditional identical module N-modular redundancy (NMR) cannot protect against Common Mode Failures (CMFs). One method that has been proposed to protect against CMFs is the use of dissimilar (diverse) module redundancy. One of the problems with previous work is that it generates these diverse modules by perturbing the gate-netlist and thus, achieve very limited diversity. In addition, previous work is very time consuming as it requires to insert fault-pairs in the gate-netlists in order to measure the effect of these on the outputs. To address these issues, this work proposes to first increase diversity by raising the level of abstraction from the gate level to the behavioral level. Secondly, we propose a fast machine learning based method that facilitates the design space exploration (DSE) of single behavioral descriptions in order to generate optimized redundant hardware accelerator system with maximum diversity to protect against CMFs. For this purpose, this work exploits one of the main advantages of C-based VLSI design: The ability to generate micro-architectures with unique characteristics from the same behavioral description by setting different synthesis directives in the form of pragmas. Experimental results show that our proposed method is a fast and efficient way to generate diverse designs to protect the system against CMFs.