Distributed and Dynamic Map-less Self-reconfiguration for Microrobot Networks

International audienceMEMS micro robots are low-power and low memory capacity devices that can sense and act. One of the most challenges in MEMS micro robot applications is the self-reconfiguration, especially when the efficiency and the scalability of the algorithm are required. In the literature, if we want a self-reconfiguration of micro robots to a target shape consisting of P positions, each micro robot should have a memory capacity of P positions. Therefore, if P equals to millions, each node should have a memory capacity of millions of positions. Therefore, this is not scalable. In this paper, nodes do not record any position, we present a self-reconfiguration method where a set of micro robots are unaware of their current position and do not have the map of the target shape. In other words, nodes do not store the positions that build the target shape. Consequently, memory usage for each node is reduced to O(1). An algorithm of self-reconfiguration to optimize the communication is deeply studied showing how to manage the dynamicity (wake up and sleep of micro robots) of the network to save energy. Our algorithm is implemented in Meld, a declarative language, and executed in a real environment simulator called DPRSim

Fitness Landscape Analysis for Scalable Multicast RRM Problem in Cellular Network

International audienceThis paper aims to solve the Radio Resource Management (RRM) problem for Multimedia Broadcast Multicast Service (MBMS) system in cellular network. We develop a flexible model to perform dynamic radio resource allocation for MBMS service by using metaheuristic approach. We conduct fitness landscape analysis to study the characteristics of the proposed model, which helps us to select appropriate search strategy. Simulation results show that the proposed algorithm provides better performance than existing algorithms. Keywords: fitness landscape, metaheuristic approach, multimedia multicast, radio resource management

Coordination and Computation in distributed intelligent MEMS

International audienceOver the last decades, research on microelectromechanical systems (MEMS) has focused on the engineering process which has led to major advances. Future challenges will consist in adding embedded intelligence to MEMS systems to obtain distributed intelligent MEMS. One intrinsic characteristic of MEMS is their ability to be mass-produced. This, however, poses scalability problems because a significant number of MEMS can be placed in a small volume. Managing this scalability requires paradigm-shifts both in hardware and software parts. Furthermore, the need for actuated synchronization, programming, communication and mobility management raises new challenges in both control and programming. Finally, MEMS are prone to faulty behaviors as they are mechanical systems and they are issued from a batch fabrication process. A new programming paradigm which can meet these challenges is therefore needed. In this article, we present CO2Dim, which stands for Coordination and Computation in Distributed Intelligent MEMS. CO2DIM is a new programming environment which includes a language based on a joint development of programming and control capabilities, a simulator and real hardware

Enhanced spread in time on-off keying technique for dense Terahertz nanonetworks

International audienceNanotechnology becomes reality paving the way for many new applications. In nanonetwork system, each nanosized device is equipped with limited capabilities and is dedicated to a basic task but the combination of the numerous devices actions results in high-level functions. In this context, large number of devices concentrated in a limited area must exchange data using wireless links. Spread in Time On-Off Keying (TS-OOK) protocol was proposed as a technique to share the radio channel over the different terahertz nano-devices. TS-OOK is based on a Femtosecond-Long pulse modulation where communication data are sent using a sequence of pulses interleaved by a constant duration randomly selected. In this paper we provide a critical analysis of the TS-OOK approach. We prove that the TS-OOK is not adaptive against the traffic load variation and induces an imbalance between the active nodes. This inequity is due to the dependency of a communication quality on the randomly chosen symbol rate. We propose a dynamic TS-OOK modulation approach, called SRH-TSOOK (Symbol rate Hopping TSOOK), where the duration between two consecutive pulses of the same transmission follows a pseudo-random sequence. We show that this approach performs better than the standard protocol when the number of active nodes increases and guarantees a better distribution of the channel capacity over the active communications. For instance, while the throughput of a communication within a TS-OOK protocol may falls bellow 105 frames/s with 300 active nodes, the throughput in the SRH-TSOOK protocol stabilizes around 207 frames/s for all the active communications. The comparison is made on the basis of probabilistic analysis allowing a numerical and accurate evaluation of the protocols performance

Scalable distributed protocol for modular micro-robots network reorganization

International audienceThe programmable material is one of the most challenging problems in micro-robot networking. In addition to the problems that raise by the miniaturization of millimeter-scale mobile devices; the conception of the distributed asynchronous algorithms allowing the coordination of large number of robots remains a very complex task. Micro-robot network represents one of the implementations of the Internet of Things, where a set of micro-robots react to an order submitted on a wireless downlink channel specifying a global goal. This goal corresponds to a target shape in the case of shape-shifting problem. Programmable materials have many applications in field of paintable displays, prototyping, locomotion, etc. We propose in this paper an original flexible distributed algorithm allowing to reorganize a modular micro-robot network into a desired target shape (phisical topology). The efficiency of such algorithm is assessed on the basis of the memory requirements, the communication load and the number of performed movements to reach the final shape. The proposed algorithm shows a great flexibility concerning the range of target shapes that can be achieved, in part because the no need for an explicit description of the final shape. To assess the computational performances of the presented algorithm, we proposed a linear programming model of the shape-shifting problem that provides a lower bounds of optimized criteria. The comparison of our results with those given by the relaxed linear programming proves the efficiency of our approach

Short and long term optimization for micro-object conveying with air-jet modular distributed system

International audienceSmart surface is a new conveying technology composed of a 2D planar surface presenting a matrix of distributed autonomous blocks. Every block contains a micro-electro-mechanical system (MEMS) actuator that controls the transfer of a possible object located above the block to the neighboring blocks, using air-jet forces. The spatial characteristics of the blocks impose some limits on the memory, energy and computation capabilities of the MEMS blocks. In the other hand, the system can reach several thousands of blocks making necessary to propose scalable algorithmic solutions.This paper studies different distributed algorithms to convey an object from an initial to a target position in the smart surface. The conveying policy emphasizes the long term use of the smart surface and the objects conveying efficiency measured by the time of the transfer. The problem stands as an original case of multi-objective Shortest Path problem (MOSP). Original because the quality of a given path is not evaluated by the sum of the weights of its segments, and because the segment weights change according to the used paths as provided by the algorithm itself. Therefore, the efficiency of a given algorithm is assessed on the basis of its performance during a long period of time.We describe here the best way to combine these two objectives and we propose a scalable incremental distributed protocol for objects conveying. The path optimality is adjusted according to the required calculation complexity. The performances of the different algorithmic and modeling variations are analyzed in terms of memory, time, computation and exchanged messages complexity. The obtained results prove the scalability of the algorithm, with linear computational, memory and convergence time complexity, and confirm the improvement of smart surface usage compared to a naive approach. The system lifespan increases of up to 130% on 40 × 40 smart surface, while the transfer cost (time and energy) is reduced. We show also that the computation time of the path with the incremental algorithm can be significantly reduced without significant degradation of the conveying system performance. For example, in a 40 × 40 smart surface, the number of messages is divided by 4 while the number of conveyed objects is only reduced by a ratio of 4%

A Shape-Shifting Distributed Meta-Algorithm for Modular Robots

International audienceNovel platforms of modular robot systems have been developed with important applications in safety, transportation and sensing domains. In such systems, modular robots are able to change their organization in order to obtain different shapes. The conception of distributed programs allowing the "optimal" reorganization of a set of robots into a specific shape appears as a very challenging problem. In this paper we present an original distributed meta-algorithm for micro-robots shape-shifting problem. We show that this meta-algorithm, described as a general functioning schema, presents a good framework to easily conceive distributed algorithms for shape-shifting problems. We also prove the facility to instantiate the algorithm for special target shapes and we give an adaptation of the algorithm to reach any horizontally convex form. The presented meta-algorithm presents two main advantages: first, there is no need to exact positioning of the robots and secondly, the memory storage and communication requirements are significantly reduced

Efficient routing protocol for concave unstable terahertz nanonetworks

International audienceThe recent progress in nanotechnologies is giving birth to a novel topology of wireless networks characterized by a high local density and an intensive node instability such as in WBAN and swarm micro-robots systems.In this paper, we show that classical and dedicated ad hoc nanonetwork routing solutions are inefficient in this case and present a low reliability level and add a supplementary delay and control traffic. Majority of these solutions are based on point to point relaying mode, which is not adapted to the instability context.The multirelay to multirelay approaches allow countering the problem of nanonodes uncertainty by using the high number of inter-node connections. However, these approaches perform badly when the nanonetwork deployment presents distortions and concave sides. We propose a new routing protocol called Multirelay to Multirelay Routing Protocol (M2MRPv2), which provides a natural way to manage the residual energy levels on the nanonodes. M2MRPv2 is, to the best of our knowledge, the only approach that proposes a proactive multirelay to multirelay routing mode where the residual energy level of the nanonodes and reliability of the routing paths are taken into account.We study the performances of multirelay to multirelay protocols according to different multi-source to multi-sink communication scenarios. The obtained results show that M2MRPv2 protocol outperforms by far the Sustainable Longevity Routing (SLR) protocol (the reference protocol for Terahertz nanonetworks) in terms of transmission reliability and energy management. This outperformance is accentuated when the Terahertz nanonetwork deployment presents many concavities

Dynamicity to Save Energy in Microrobots Reconfiguration

International audienceIn this paper we present a dynamic self reconfiguration protocol for MEMS micro robots. The protocol presented in this paper is without map of the target shape which makes it efficient and scalable. In other words, nodes do not store the positions that build the target shape. Consequently, memory usage for each node is reduced to a constant complexity. An algorithm of self-reconfiguration is deeply studied showing how to manage the dynamicity (wake up and sleep of micro robots)of the network to save energy. Our algorithm is implemented in Meld, a declarative language, and executed in a real environment simulator called DPRSim