Using minimal communication to improve decentralized conflict resolution for non-holonomic vehicles

This paper addresses the time-varying formation-containment (FC) problem for general linear multi-agent systems based on an observer viewpoint under the directed communication graph which contains a spanning tree. A new format of time-varying formation shapes with the properties of translation, scalability and rotation is proposed. Then the time-varying formation tracking problem where the real leader's input is unknown to all other agents is solved independently. After that, the time-varying FC problem where the challenge is how to deal with the formation-achieving agents' unknown nonzero inputs for containment-achieving agents, is firstly addressed. All the designed controllers, which need no eigenvalue information of the whole graph, are fully distributed and so can be applied to large-scale systems. The influence of communication graph structure to the control convergence rate is further analysed. The above theoretical results are verified by multiple nonholonomic vehicles in simulations.

Efficient access to spectrum is critical to maintain reliable and robust communication in military networks, especially for ground vehicles on the move. High mobility and frequent topology variations make spectrum management in battlefields challenging. In this paper, we present a decentralized, hierarchical approach to assign spectrum channels among vehicles in a fair and efficient manner. Making use of group mobility, we propose a low-complexity allocation scheme with minimum communication and computation overhead. Experimental results demonstrate that the proposed algorithm can reduce the overhead by 10+ fold with maintaining reasonable spectrum utilization.

In this paper, we present a decentralized trajectory tracking control with collision avoidance for an arbitrarily large group of heterogeneous, nonholonomic vehicles. We consider vehicles with different constant speeds and bounded turning rates (e.g., airplanes), for which their avoidance maneuverability is limited. The proposed controller is divided in two parts: an auxiliary system and a local heading control. The auxiliary system is in charge of guiding the vehicle toward the desired trajectory while guaranteeing collision avoidance with other agents at all times. The local heading control is designed such that the vehicle remains continuously within a bounded, short distance of the auxiliary system. To enforce the convergence of the vehicles to a proximity of their desired trajectories and avoid deadlocks (a common issue within most decentralized navigation methods), an alternative discontinuous control strategy is presented. Finally, a numerical example is provided to illustrate the performance of the proposed control strategy.

Flexible heat exchanger network design for chemical processes with operation mode changes

Tree-structured computations are relatively easy to process in parallel. As leaf processes are recursively spawned they can be assigned to independent processors in a multicomputer network. However, to achieve good performance the on-line mapping algorithm must maintain load balance, i.e., distribute processes equitably among processors. Additionally, the algorithm itself must be distributed in nature, and process allocation must be completed via message-passing with minimal communication overhead. This paper investigates bounds on the performance of deterministic and randomized algorithms for on-line tree embeddings. In particular, we study trade-offs between computation overhead (load imbalance) and communication overhead (message congestion). We give a simple technique to derive lower bounds on the congestion that any on-line allocation algorithm must incur in order to guarantee load balance. This technique works for both randomized and deterministic algorithms. We prove that the advantage of randomization is limited. Optimal bounds are achieved for several networks, including multidimensional grids and butterflies.

Tripartite (Diffie-Hellman) Key Exchange (3KE), introduced by Joux (ANTS-IV 2000), represents today the only known class of group key exchange protocols, in which computation of unauthenticated session keys requires one round and proceeds with minimal computation and communication overhead. The first one-round authenticated 3KE version that preserved the unique efficiency properties of the original protocol and strengthened its security towards resilience against leakage of ephemeral (session-dependent) secrets was proposed recently by Manulis, Suzuki, and Ustaoglu (ICISC 2009).In this work we explore sufficient conditions for building such protocols. We define a set of admissible polynomials and show how their construction generically implies 3KE protocols with the desired security and efficiency properties. Our result generalizes the previous 3KE protocol and gives rise to many new authenticated constructions, all of which enjoy forward secrecy and resilience to ephemeral key-leakage under the gap Bilinear Diffie-Hellman assumption in the random oracle model.

This paper considers the problem of multi-agent distributed optimization. In this problem, there are multiple agents in the system, and each agent only knows its local cost function. The objective for the agents is to collectively compute a common minimum of the aggregate of all their local cost functions. In principle, this problem is solvable using a distributed variant of the traditional gradient-descent method, which is an iterative method. However, the speed of convergence of the traditional gradient-descent method is highly influenced by the conditioning of the optimization problem being solved. Specifically, the method requires a large number of iterations to converge to a solution if the optimization problem is ill-conditioned. In this paper, we propose an iterative pre-conditioning approach that can significantly attenuate the influence of the problem's conditioning on the convergence-speed of the gradient-descent method. The proposed pre-conditioning approach can be easily implemented in distributed systems and has minimal computation and communication overhead. For now, we only consider a specific distributed optimization problem wherein the individual local cost functions of the agents are quadratic. Besides the theoretical guarantees, the improved convergence speed of our approach is demonstrated through experiments on a real data-set.

Support for intelligent, autonomous, adaptive and distributed resource management is a key to the success of scalable and dynamic wireless sensor network applications. Distributed independent reinforcement learning (DIRL) is a micro-learning framework that enables distributed, adaptive resource management using only local information at individual sensor nodes. In this paper we propose COllective INtelligence (COIN) a macro-learning paradigm that aims to specifically address the problem of designing utility functions for individual agents in order to achieve higher system wide utility. We extend DIRL, by combining it with COIN based macro-learning paradigm to steer the system towards global optimization, improving performance with minimal communication overheads. We present results of simulation to compare our approach with other existing approaches such as team game and DIRL in an example object tracking application. Simulation results demonstrate that a combination of micro- and macro-learners is two times more energy-efficient than micro-learners (DIRL) alone and four times more energy-efficient than macro-learners (TEAM game) alone.

A novel control strategy for mode seamless switching of PV converter in DC microgrid based on double integral sliding mode control

In this paper, we propose an efficient technique for run-time application mapping onto Network-on-Chip (NoC) platforms with multiple voltage levels. Our technique consists of a region selection algorithm and a heuristic for run-time application mapping which minimizes the communication energy consumption, while still providing the required performance guarantees. The proposed technique allows for new applications to be easily added to the system platform with minimal inter-processor communication overhead. Moreover, our approach scales very well for large designs. Finally, the experimental results show as much as 50% communication energy savings compared to arbitrary mapping solutions.

In this paper, we consider the problem of collision-free motion planning for multiple nonholonomic planar vehicles. Each vehicle is capable of moving at constant speed along paths with bounded curvature, and is aware of the position and heading of other vehicles within a certain sensing radius. No other information exchange is required between vehicles. We propose a spatially decentralized, cooperative hybrid control policy that ensures safety for arbitrary numbers of vehicles. Furthermore, we show that under certain conditions, the policy avoids dead- and livelock, and eventually all vehicles reach their intended targets. Simulations and experimental results are presented and discussed.

The simple reactor model developed for the fluidized-bed methanator PEDU gives reasonably good parity plots for six PEDU tests using six different catalysts. This model can be used to predict the performance of the pilot plant methanator and as a building block in any computerized simulation of the BI-GAS process for process development, design or optimization purposes. Some refinements could be made to the model to accommodate changes in mode of operation and additional knowledge gained concerning the hydrodynamic properties of the catalyst bed. The kinetic model, based upon a first-order rate equation to describe the catalyst behavior in the PEDU, also appears to be satisfactory as to its utilization in the reactor model. Further refinements could be made to yield a more mechanistically accurate expression, which would include the effects of non-first-order kinetics and deactivation on CO conversion and of selectivity on product distribution. The selectivity of molybdenum-containing catalysts for the water-gas shift reaction has been shown to be significantly higher than that of cobalt-containing catalysts. This suggests that catalysts containing molybdenum might be more suitable for processes in which the water-gas shift reaction must be combined with methanation. However, this increase in selectivity appears to be coupled withmore » a reduction in overall activity. Further investigation is neededto determine whether this reduction is real or merely the result of an imbalance between particle size and pore structure of the molybdenum-containing catalyst, which has resulted in mass-transfer limitations in those catalysts tested so far.« less

The data distribution problem is very complex, because it involves trade-off decisions between minimizing communication and maximizing parallelism. A common approach towards solving this problem is to break the data mapping into two stages: an alignment stage and a distribution stage. The alignment stage attempts to increase parallelism, while the distribution stage attempts to decrease communication overhead. As opposed to previous approaches, we consider the alignment and distribution problems in a unified framework, and attempt to simultaneously maximize parallelism and minimize communication overhead. The problem becomes harder if dynamic remapping, multi-dimensional distributions, array replications and control flow are taken into account. This paper formulates the full data decomposition problem that addresses all these issues and presents a simple new algorithm to find the optimal solution of the dynamic data distribution problem, given the number of processors and a partitioning of the input program into phases. The algorithm runs efficiently for small search spaces (several hundreds of data distributions).

Self-optimization enables technical systems to adapt their behavior to varying environmental conditions and changing operation modes. Objective functions serve as evaluation criteria for the system behavior. In this paper we present a novel approach of an objective-based controller. This controller is based on Pareto sets, which are solutions of multiobjective optimization problems and computed offline. The controller can be used to continuously adjust the system behavior by computing optimal configurations out of the Pareto sets without solving an optimization problem at runtime. The goal of the controller is to drive the objective values toward a desired relative weighting. Furthermore, the controller is able to cope with varying operation modes, which arise in case of component faults, for example. For each operation mode an entire Pareto set is computed separately. For designing the objective-based controller we use a simplified model of the closed-loop system. The objective values are approximated at runtime by means of a lowpass filter. An active suspension system affected by unknown track excitations serves as an application example. We use a particular control reconfiguration approach in case of an actuator fault as a change of the operation mode. Finally, simulations with a nonlinear model of the system validate our approach.

The smart water monitoring system (SWMS) integrated with IoT provides improved services to the society with minimal effort. At the same time, IoT connectivity brings various active, passive, and physical security threats to the system. The conventional cryptosystems are infeasible for resource-constrained IoT devices and susceptible to physical attacks. Physically unclonable function (PUF) emerged as a low-cost, convenient hardware security primitive. In this work, we have proposed a secure (against active, passive, and physical attacks) authentication and key sharing protocol for the SWMS with low overhead. The extensive security analysis illustrates the durability of the protocol. The performance analysis shows the proposed protocol's minimal computation, communication overhead, and resource utilization. Using a mathematical PUF model (i.e., soft model) reduces the server-side burden of storing PUF challenge-response pairs. Moreover, the protocol deals with the noisy PUF responses to maintain the correctness and accuracy of the authentication process. Finally, a comparison with the existing works establishes the proposed protocol's superiority in the SWMS.