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Users of device-to-device (D2D) communication need efficient content discovery mechanisms to steer their requests toward the node in their neighborhood that is most likely to satisfy them. The problem is further compounded by the lack of a central coordination entity as well as by the inherent mobility of devices, which leads to volatile topologies. In this paper, we first discuss group-based communication among non-rooted Android devices using Wi-Fi direct, a protocol recently standardized by the Wi-Fi alliance. We propose intra- and inter-group communication methodologies, which we validate through a simple testbed where content-centric routing is used. Next, we address the autonomous formation of groups with the goal of achieving efficient device resource utilization as well as full connectivity. Finally, we evaluate the performance of our group formation procedure both in simulation and in a real testbed involving Android devices in different topologies.

Micro and nanorobotics represents one of the most challenging sectors of modern robotics. Through batch fabrication of Micro Electro-Mechanical Systems (MEMS), advanced small scale sensing and actuating tasks in a wide area of applications can be performed. Most miniaturized electro-mechanical devices are characterized by low-power and low-memory capacity. The huge number of modular robots introduces the need to explore novel self-reconfiguration algorithms to optimize movement and communication performances in terms of efficiency, parallelism and scalability. Nano-transceivers and nano-antennas operating in the Terahertz Band are already a well acquainted communication paradigm, enforcing nano-wireless networking that can be directly integrated in MEMS microrobots. Several logical topology shape-shifting algorithms are already implemented and tested in literature, along with performance evaluation on nano-wireless use. This article aims to provide an algorithm to reconnect groups of microrobots, along with a novel movement model for microrobotics ensembles introduced to enforce more realistic simulations. Special emphasis is given on the need of novel movement algorithms for swarms of microrobots.

Among all the new robotics technologies, great interest is rising in the field of microrobotics. Micro Electro-Mechanical Systems (MEMS) microrobots are miniaturized electro-mechanical devices that can perform various tasks in a wide area of applications. Despite the low-power and low-memory capacity, they are provided with sensors and actuators. Self-reconfiguration is a key factor for MEMS microrobots to perform their tasks and to optimize their communications in order to achieve efficiency, parallelism and scalability. Nano-transceivers and nano-antennas operating in the Terahertz Band offer a promising communication paradigm, providing nanowireless networking directly integrated in MEMS microrobots. Catoms from Claytronics project are an appropriate microrobotics case to explore this novel framework. Several logical topology shape-shifting algorithms have been implemented and tested, along with different nano-wireless simulations. This paper aims to provide a survey on nano-wireless communication for modular robotics and propose some optimization choices. Special emphasis is given to the use of the nano-wireless communications for topology formation and maintenance in microrobotics.

Wireless Sensor Networks are traditionally composed of a multiplicity of sensor nodes that sense given phenomena and deliver the sensed data to specific sink nodes. In the most of the application scenarios, sensor nodes have been considered motionless. On the contrary, interesting possibilities arise if some sensors are embedded in devices carried by mobile agents as people, cars, animals, etc. If sinks move within the considered sensor field, they are able to provide both sparse sensing and collecting of data measured by static sensors placed at fixed locations. The main goal of this work is to evaluate, through simulations, the impact of sinks' mobility in a wireless sensor network created by using the topology formation mechanism provided by the IEEE 802.15.4 Standard. To this aim, as a practical case study, we consider a wireless sensor network deployed in a museum used to monitor the presence, the localization and other parameters of artworks exposed in it. In this context, we analyze how sinks' mobility affects connectivity and energy consumption for network formation and re-configuration.

The IEEE 802.15.4 standard defines a set of procedures to set-up a low-rate wireless personal area network where nodes self-organize into a logical communication structure through which data can be routed, hop by hop, from sources to destinations. The network formation of the IEEE 802.15.4 does not impose constraints on the topology. The Zigbee alliance uses the IEEE 802.15.4 layers to build a complete protocol stack for the implementation of wireless sensor networks. ZigBee specifies the network layer for star, tree and peer-to-peer topologies. Starting from these, more complex cluster-tree topologies can be formed. To control the network topology ZigBee fixes the maximum number of routers and end-devices that each router may have as children and also fixes the maximum depth of the tree. To better understand the importance of these constraints we simulate and analyze the IEEE 802.15.4 formation procedure in different network settings (single-sink and multi- sink scenarios). The goal is to provide guidelines for the practical implementation of ZigBee network formation with the aforementioned constraints.

This paper investigates the topology formation mechanisms provided by IEEE 802.15.4 to create tree-based topologies, in the context of a multi-sink wireless sensor network. the topology formation protocol is simulated starting from a random deployment of a given number of nodes, to obtain statistics of the position of those nodes belonging to given tree levels. It is shown that under some circumstances the nodes belonging to any level can be assumed to be uniformly distributed over the plane. Under such assumption, a mathematical formulation is used to optimize the average number of children per parent and the number of levels in the tree (that is, the tree height), through maximization of the network association probability