On the Role of Mobility for Multi-message Gossip

We consider information dissemination in a large $n$-user wireless network in which $k$ users wish to share a unique message with all other users. Each of the $n$ users only has knowledge of its own contents and state information; this corresponds to a one-sided push-only scenario. The goal is to disseminate all messages efficiently, hopefully achieving an order-optimal spreading rate over unicast wireless random networks. First, we show that a random-push strategy -- where a user sends its own or a received packet at random -- is order-wise suboptimal in a random geometric graph: specifically, $\Omega(\sqrt{n})$ times slower than optimal spreading. It is known that this gap can be closed if each user has "full" mobility, since this effectively creates a complete graph. We instead consider velocity-constrained mobility where at each time slot the user moves locally using a discrete random walk with velocity $v(n)$ that is much lower than full mobility. We propose a simple two-stage dissemination strategy that alternates between individual message flooding ("self promotion") and random gossiping. We prove that this scheme achieves a close to optimal spreading rate (within only a logarithmic gap) as long as the velocity is at least $v(n)=\omega(\sqrt{\log n/k})$. The key insight is that the mixing property introduced by the partial mobility helps users to spread in space within a relatively short period compared to the optimal spreading time, which macroscopically mimics message dissemination over a complete graph.Comment: accepted to IEEE Transactions on Information Theory, 201

Formal analysis techniques for gossiping protocols

We give a survey of formal verification techniques that can be used to corroborate existing experimental results for gossiping protocols in a rigorous manner. We present properties of interest for gossiping protocols and discuss how various formal evaluation techniques can be employed to predict them

A survey of flooding, gossip routing, and related schemes for wireless multi- hop networks

Flooding is an essential and critical service in computer networks that is used by many routing protocols to send packets from a source to all nodes in the network. As the packets are forwarded once by each receiving node, many copies of the same packet traverse the network which leads to high redundancy and unnecessary usage of the sparse capacity of the transmission medium. Gossip routing is a well-known approach to improve the flooding in wireless multi-hop networks. Each node has a forwarding probability p that is either statically per-configured or determined by information that is available at runtime, e.g, the node degree. When a packet is received, the node selects a random number r. If the number r is below p, the packet is forwarded and otherwise, in the most simple gossip routing protocol, dropped. With this approach the redundancy can be reduced while at the same time the reachability is preserved if the value of the parameter p (and others) is chosen with consideration of the network topology. This technical report gives an overview of the relevant publications in the research domain of gossip routing and gives an insight in the improvements that can be achieved. We discuss the simulation setups and results of gossip routing protocols as well as further improved flooding schemes. The three most important metrics in this application domain are elaborated: reachability, redundancy, and management overhead. The published studies used simulation environments for their research and thus the assumptions, models, and parameters of the simulations are discussed and the feasibility of an application for real world wireless networks are highlighted. Wireless mesh networks based on IEEE 802.11 are the focus of this survey but publications about other network types and technologies are also included. As percolation theory, epidemiological models, and delay tolerant networks are often referred as foundation, inspiration, or application of gossip routing in wireless networks, a brief introduction to each research domain is included and the applicability of the particular models for the gossip routing is discussed

EUSN 2021 Book of Abstracts, Fifth European Conference on Social Networks

Book of abstract of the fifth European conference on Social Networks EUSN 202

Cooperative Strategies for Near-Optimal Computation in Wireless Networks

Computation problems, such as network coding and averaging consen- sus, have become increasingly central to the study of wireless networks. Network coding, in which intermediate terminals compute and forward functions of others’ messages, is instrumental in establishing the capacity of multicast networks. Averaging consensus, in which terminals compute the mean of others’ measurements, is a canonical building block of dis- tributed estimation over sensor networks. Both problems, however, are typically studied over graphical networks, which abstract away the broad- cast and superposition properties fundamental to wireless propagation. The performance of computation in realistic wireless environments, there- fore, remains unclear. In this thesis, I seek after near-optimal computation strategies under realistic wireless models. For both network coding and averaging con- sensus, cooperative communications plays a key role. For network cod- ing, I consider two topologies: a single-layer network in which users may signal cooperatively, and a two-transmitter, two-receiver network aided by a dedicated relay. In the former topology, I develop a decode-and- forward scheme based on a linear decomposition of nested lattice codes. For a network having two transmitters and a single receiver, the proposed scheme is optimal in the diversity-multiplexing tradeo↵; otherwise it pro- vides significant rate gains over existing non-cooperative approaches. In the latter topology, I show that an amplify-and-forward relay strategy is optimal almost everywhere in the degrees-of-freedom. Furthermore, for symmetric channels, amplify-and-forward achieves rates near capacity for a non-trivial set of channel gains. For averaging consensus, I consider large networks of randomly-placed nodes. Under a path-loss wireless model, I characterize the resource de- mands of consensus with respect to three metrics: energy expended, time elapsed, and time-bandwidth product consumed. I show that existing con- sensus strategies, such as gossip algorithms, are nearly order optimal in the energy expended but strictly suboptimal in the other metrics. I propose a new consensus strategy, tailored to the wireless medium and cooperative in nature, termed hierarchical averaging. Hierarchical averaging is nearly order optimal in all three metrics for a wide range of path-loss exponents. Finally, I examine consensus under a simple quantization model, show- ing that hierarchical averaging achieves a nearly order-optimal tradeo↵ between resource consumption and estimation accuracy

THE EFFECT OF INTERACTIONS BETWEEN PROTOCOLS AND PHYSICAL TOPOLOGIES ON THE LIFETIME OF WIRELESS SENSOR NETWORKS

Wireless sensor networks enable monitoring and control applications such weather sensing, target tracking, medical monitoring, road monitoring, and airport lighting. Additionally, these applications require long term and robust sensing, and therefore require sensor networks to have long system lifetime. However, sensor devices are typically battery operated. The design of long lifetime networks requires efficient sensor node circuits, architectures, algorithms, and protocols. In this research, we observed that most protocols turn on sensor radios to listen or receive data then make a decision whether or not to relay it. To conserve energy, sensor nodes should consider not listening or receiving the data when not necessary by turning off the radio. We employ a cross layer scheme to target at the network layer issues. We propose a simple, scalable, and energy efficient forwarding scheme, which is called Gossip-based Sleep Protocol (GSP). Our proposed GSP protocol is designed for large low-cost wireless sensor networks with low complexity to reduce the energy cost for every node as much as possible. The analysis shows that allowing some nodes to remain in sleep mode improves energy efficiency and extends network lifetime without data loss in the topologies such as square grid, rectangular grid, random grid, lattice topology, and star topology. Additionally, GSP distributes energy consumption over the entire network because the nodes go to sleep in a fully random fashion and the traffic forwarding continuously via the same path can be avoided

Decentralized data fusion and data harvesting framework for heterogeneous dynamic network systems

Diese Dissertation behandelt das Thema der dezentralisieren Sammlung und Fusion von Daten in heterogenen, ressourcenbeschraekten und dynamischen Netzwerkszenarien. Dazu wird ein generisches Framework vorgestellt, dass es erlaubt die Datensammlung, den Datenaustausch und auch die Datenfusion dynamisch zu konfigurieren. Im Zuge dessen wird auch eine Methode zur gerichteten Fusion von Daten auf graphentheoretischer Basis eingefrt, die es erlaubt eine logische Struktur fuer die Fusion von Informationen zu modellieren. Eine Markup-Sprache, die sowohl menschen- als auch maschinenlesbar ist, erlaubt es diese Struktur leicht zu editieren. Im Bereich der Protokolle zum Datenaustausch liegt der Fokus dieser Arbeit auf Energieeffizienz, um auch ressourcenbeschraenkte Geraete einzubinden. Ein weiterer Schwerpunkt liegt auf Robustheit fuer die betrachteten dynamischen Szenarien. Diese Dissertation schlaet zudem Design-Richtlinien vor, um verschiedene Ziele fuer unterschiedliche Applikationen umzusetzen. Diese lassen sich leicht in das vorgestellte Framework integrieren und darueber konfigurieren. Dadurch ergibt sich im Ganzen eine flexible Architektur, die sich leicht an dynamische Umgebungen anpassen laesst.With the increasing number of available smart phones, sensor nodes, and novel mobile smart devices such as Google glass, a large volume of data reflecting the environment is generated in the form of sensing data sources (such as GPS, received signal strength identification, accelerometer, microphone, images, videos and gyroscope, etc.). Some context-aware and data centric applications require the online processing of the data collected. The thesis researches on the decentralized data fusion and data harvesting framework for heterogeneous dynamic network system consisting of various devices with resource constraints. In order to achieve the flexible design, a general architecture is provided while the detailed data fusion and data exchange functions can be dynamically configured. A novel method to use directed fusion graph to model the logical structure of the distributed information fusion architecture is introduced. This directed fusion graph can accurately portray the interconnection among different data fusion components and the data exchange protocols, as well as the detailed data streams. The directed fusion graph is then transformed into a format with marked language, so that both human and machine can easily understand and edit. In the field of data exchange protocols, this thesis targets energy-efficiency considering the resource constraints of the devices and robustness, as the dynamic environment might cause failures to the system. It proposes a refined gossip strategy to reduce retransmission of redundant data. The thesis also suggests a design guideline to achieve different design aims for different applications. These results in this field can be integrated into the framework effortlessly. The configuration mechanism is another feature of this framework. Different from other research work which consider configuration as a post-design work separated from the main design of any middle-ware. This thesis considers the configuration part as another dimension of the framework. The whole strategy in configuration sets up the foundation for the flexible architecture, and makes it easy to adapt to the dynamic environment. The contributions in the above fields lead to a light-weight data fusion and data harvesting framework which can be deployed easily above wireless based, heterogeneous, dynamic network systems, even in extreme conditions, to handle data-centric applications

Reliable & Efficient Data Centric Storage for Data Management in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have become a mature technology aimed at performing environmental monitoring and data collection. Nonetheless, harnessing the power of a WSN presents a number of research challenges. WSN application developers have to deal both with the business logic of the application and with WSN's issues, such as those related to networking (routing), storage, and transport. A middleware can cope with this emerging complexity, and can provide the necessary abstractions for the definition, creation and maintenance of applications. The final goal of most WSN applications is to gather data from the environment, and to transport such data to the user applications, that usually resides outside the WSN. Techniques for data collection can be based on external storage, local storage and in-network storage. External storage sends data to the sink (a centralized data collector that provides data to the users through other networks) as soon as they are collected. This paradigm implies the continuous presence of a sink in the WSN, and data can hardly be pre-processed before sent to the sink. Moreover, these transport mechanisms create an hotspot on the sensors around the sink. Local storage stores data on a set of sensors that depends on the identity of the sensor collecting them, and implies that requests for data must be broadcast to all the sensors, since the sink can hardly know in advance the identity of the sensors that collected the data the sink is interested in. In-network storage and in particular Data Centric Storage (DCS) stores data on a set of sensors that depend on a meta-datum describing the data. DCS is a paradigm that is promising for Data Management in WSNs, since it addresses the problem of scalability (DCS employs unicast communications to manage WSNs), allows in-network data preprocessing and can mitigate hot-spots insurgence. This thesis studies the use of DCS for Data Management in middleware for WSNs. Since WSNs can feature different paradigms for data routing (geographical routing and more traditional tree routing), this thesis introduces two different DCS protocols for these two different kinds of WNSs. Q-NiGHT is based on geographical routing and it can manage the quantity of resources that are assigned to the storage of different meta-data, and implements a load balance for the data storage over the sensors in the WSN. Z-DaSt is built on top of ZigBee networks, and exploits the standard ZigBee mechanisms to harness the power of ZigBee routing protocol and network formation mechanisms. Dependability is another issue that was subject to research work. Most current approaches employ replication as the mean to ensure data availability. A possible enhancement is the use of erasure coding to improve the persistence of data while saving on memory usage on the sensors. Finally, erasure coding was applied also to gossiping algorithms, to realize an efficient data management. The technique is compared to the state-of-the-art to identify the benefits it can provide to data collection algorithms and to data availability techniques