An event-based architecture for solving constraint satisfaction problems

Constraint satisfaction problems (CSPs) are typically solved using conventional von Neumann computing architectures. However, these architectures do not reflect the distributed nature of many of these problems and are thus ill-suited to solving them. In this paper we present a hybrid analog/digital hardware architecture specifically designed to solve such problems. We cast CSPs as networks of stereotyped multi-stable oscillatory elements that communicate using digital pulses, or events. The oscillatory elements are implemented using analog non-stochastic circuits. The non-repeating phase relations among the oscillatory elements drive the exploration of the solution space. We show that this hardware architecture can yield state-of-the-art performance on a number of CSPs under reasonable assumptions on the implementation. We present measurements from a prototype electronic chip to demonstrate that a physical implementation of the proposed architecture is robust to practical non-idealities and to validate the theory proposed.Comment: First two authors contributed equally to this wor

A Systematic Approach to Constructing Incremental Topology Control Algorithms Using Graph Transformation

Communication networks form the backbone of our society. Topology control algorithms optimize the topology of such communication networks. Due to the importance of communication networks, a topology control algorithm should guarantee certain required consistency properties (e.g., connectivity of the topology), while achieving desired optimization properties (e.g., a bounded number of neighbors). Real-world topologies are dynamic (e.g., because nodes join, leave, or move within the network), which requires topology control algorithms to operate in an incremental way, i.e., based on the recently introduced modifications of a topology. Visual programming and specification languages are a proven means for specifying the structure as well as consistency and optimization properties of topologies. In this paper, we present a novel methodology, based on a visual graph transformation and graph constraint language, for developing incremental topology control algorithms that are guaranteed to fulfill a set of specified consistency and optimization constraints. More specifically, we model the possible modifications of a topology control algorithm and the environment using graph transformation rules, and we describe consistency and optimization properties using graph constraints. On this basis, we apply and extend a well-known constructive approach to derive refined graph transformation rules that preserve these graph constraints. We apply our methodology to re-engineer an established topology control algorithm, kTC, and evaluate it in a network simulation study to show the practical applicability of our approachComment: This document corresponds to the accepted manuscript of the referenced journal articl

Memory and information processing in neuromorphic systems

A striking difference between brain-inspired neuromorphic processors and current von Neumann processors architectures is the way in which memory and processing is organized. As Information and Communication Technologies continue to address the need for increased computational power through the increase of cores within a digital processor, neuromorphic engineers and scientists can complement this need by building processor architectures where memory is distributed with the processing. In this paper we present a survey of brain-inspired processor architectures that support models of cortical networks and deep neural networks. These architectures range from serial clocked implementations of multi-neuron systems to massively parallel asynchronous ones and from purely digital systems to mixed analog/digital systems which implement more biological-like models of neurons and synapses together with a suite of adaptation and learning mechanisms analogous to the ones found in biological nervous systems. We describe the advantages of the different approaches being pursued and present the challenges that need to be addressed for building artificial neural processing systems that can display the richness of behaviors seen in biological systems.Comment: Submitted to Proceedings of IEEE, review of recently proposed neuromorphic computing platforms and system

Mitigation of packet loss with end-to-end delay in wireless body area network applications

The wireless body area network (WBAN) has been proposed to offer a solution to the problem of population ageing, shortage in medical facilities and different chronic diseases. The development of this technology has been further fueled by the demand for real-time application for monitoring these cases in networks. The integrity of communication is constrained by the loss of packets during communication affecting the reliability of WBAN. Mitigating the loss of packets and ensuring the performance of the network is a challenging task that has sparked numerous studies over the years. The WBAN technology as a problem of reducing network lifetime; thus, in this paper, we utilize cooperative routing protocol (CRP) to improve package delivery via end-to-end latency and increase the length of the network lifetime. The end-to-end latency was used as a metric to determine the significance of CRP in WBAN routing protocols. The CRP increased the rate of transmission of packets to the sink and mitigate packet loss. The proposed solution has shown that the end-to-end delay in the WBAN is considerably reduced by applying the cooperative routing protocol. The CRP technique attained a delivery ratio of 0.8176 compared to 0.8118 when transmitting packets in WBAN

Optimal and Efficient Decision-Making for Power System Expansion Planning

A typical power system consists of three major sectors: generation, transmission, and distribution. Due to ever increasing electricity consumption and aging of the existing components, generation, transmission, and distribution systems and equipment must be analyzed frequently and if needed be replaced and/or expanded timely. By definition, the process of power system expansion planning aims to decide on new as well as upgrading existing system components in order to adequately satisfy the load for a foreseen future. In this dissertation, multiple economically optimal and computationally efficient methods are proposed for expanding power generation, transmission, and distribution systems. First, a computationally efficient model is proposed for transmission expansion planning (TEP). While the existing TEP models use bus voltage angles, the proposed TEP takes advantages of linear sensitivity factors to omit voltage angles from the formulation and replace all nodal power balance constraints by one equivalent constraint. Simulation results show that the proposed model provides the same results as the classical angle-based model while being much faster. Second, a distributed collaborative TEP algorithm for interconnected multi-regional power systems is proposed. The information privacy is respected as each local planner shares limited information related to cross-border tie-lines with its neighboring planners. To coordinate the local planners, a two-level distributed optimization algorithm is proposed based on the concept of analytical target cascading for multidisciplinary design optimization. Third, a security-constrained generation and transmission expansion planning (G&TEP) model with respect to the risk of possible N-1 contingencies is proposed. Using the concept of risk, non-identical probability and severity of individual contingencies are modeled in the proposed G&TEP model. Finally, a mixed-integer linear programming model is proposed for resilient feeder routing in power distribution systems. Geographical information system (GIS) data is used in the proposed model. As it is proven, having GIS facilities will lead to a more cost-efficient and resilient feeder routing scheme than the scheme obtained using electrical points. The proposed model and solution algorithm are comprehensive from several practical aspects such as economic objectives (installation cost, power losses, resiliency), technical constraints (voltage drops, radially constraint, reliability), and geographical constraints (obstacles, right-of-ways)