From Dumb Wireless Sensors to Smart Networks using Network Coding

The vision of wireless sensor networks is one of a smart collection of tiny, dumb devices. These motes may be individually cheap, unintelligent, imprecise, and unreliable. Yet they are able to derive strength from numbers, rendering the whole to be strong, reliable and robust. Our approach is to adopt a distributed and randomized mindset and rely on in network processing and network coding. Our general abstraction is that nodes should act only locally and independently, and the desired global behavior should arise as a collective property of the network. We summarize our work and present how these ideas can be applied for communication and storage in sensor networks.Comment: To be presented at the Inaugural Workshop of the Center for Information Theory and Its Applications, University of California - San Diego, La Jolla, CA, February 6 - 10, 200

Enhancing multi-source content delivery in content-centric networks with fountain coding

Fountain coding has been considered as especially suitable for lossy environments, such as wireless networks, as it provides redundancy while reducing coordination overheads between sender(s) and receiver(s). As such it presents beneficial properties for multi-source and/or multicast communication. In this paper we investigate enhancing/increasing multi-source content delivery efficiency in the context of Content-Centric Networking (CCN) with the usage of fountain codes. In particular, we examine whether the combination of fountain coding with the in-network caching capabilities of CCN can further improve performance. We also present an enhancement of CCN's Interest forwarding mechanism that aims at minimizing duplicate transmissions that may occur in a multi-source transmission scenario, where all available content providers and caches with matching (cached) content transmit data packets simultaneously. Our simulations indicate that the use of fountain coding in CCN is a valid approach that further increases network performance compared to traditional schemes

Towards video streaming in IoT environments: vehicular communication perspective

Multimedia oriented Internet of Things (IoT) enables pervasive and real-time communication of video, audio and image data among devices in an immediate surroundings. Today's vehicles have the capability of supporting real time multimedia acquisition. Vehicles with high illuminating infrared cameras and customized sensors can communicate with other on-road devices using dedicated short-range communication (DSRC) and 5G enabled communication technologies. Real time incidence of both urban and highway vehicular traffic environment can be captured and transmitted using vehicle-to-vehicle and vehicle-to-infrastructure communication modes. Video streaming in vehicular IoT (VSV-IoT) environments is in growing stage with several challenges that need to be addressed ranging from limited resources in IoT devices, intermittent connection in vehicular networks, heterogeneous devices, dynamism and scalability in video encoding, bandwidth underutilization in video delivery, and attaining application-precise quality of service in video streaming. In this context, this paper presents a comprehensive review on video streaming in IoT environments focusing on vehicular communication perspective. Specifically, significance of video streaming in vehicular IoT environments is highlighted focusing on integration of vehicular communication with 5G enabled IoT technologies, and smart city oriented application areas for VSV-IoT. A taxonomy is presented for the classification of related literature on video streaming in vehicular network environments. Following the taxonomy, critical review of literature is performed focusing on major functional model, strengths and weaknesses. Metrics for video streaming in vehicular IoT environments are derived and comparatively analyzed in terms of their usage and evaluation capabilities. Open research challenges in VSV-IoT are identified as future directions of research in the area. The survey would benefit both IoT and vehicle industry practitioners and researchers, in terms of augmenting understanding of vehicular video streaming and its IoT related trends and issues

Collaborative Communication And Storage In Energy-Synchronized Sensor Networks

In a battery-less sensor network, all the operation of sensor nodes are strictly constrained by and synchronized with the fluctuations of harvested energy, causing nodes to be disruptive from network and hence unstable network connectivity. Such wireless sensor network is named as energy-synchronized sensor networks. The unpredictable network disruptions and challenging communication environments make the traditional communication protocols inefficient and require a new paradigm-shift in design. In this thesis, I propose a set of algorithms on collaborative data communication and storage for energy-synchronized sensor networks. The solutions are based on erasure codes and probabilistic network codings. The proposed set of algorithms significantly improve the data communication throughput and persistency, and they are inherently amenable to probabilistic nature of transmission in wireless networks. The technical contributions explore collaborative communication with both no coding and network coding methods. First, I propose a collaborative data delivery protocol to exploit the optimal performance of multiple energy-synchronized paths without network coding, i.e. a new max-flow min-variance algorithm. In consort with this data delivery protocol, a localized TDMA MAC protocol is designed to synchronize nodes\u27 duty-cycles and mitigate media access contentions. However, the energy supply can change dynamically over time, making determined duty cycles synchronization difficult in practice. A probabilistic approach is investigated. Therefore, I present Opportunistic Network Erasure Coding protocol (ONEC), to collaboratively collect data. ONEC derives the probability distribution of coding degree in each node and enable opportunistic in-network recoding, and guarantee the recovery of original sensor data can be achieved with high probability upon receiving any sufficient amount of encoded packets. Next, OnCode, an opportunistic in-network data coding and delivery protocol is proposed to further improve data communication under the constraints of energy synchronization. It is resilient to packet loss and network disruptions, and does not require explicit end-to-end feedback message. Moreover, I present a network Erasure Coding with randomized Power Control (ECPC) mechanism for collaborative data storage in disruptive sensor networks. ECPC only requires each node to perform a single broadcast at each of its several randomly selected power levels. Thus it incurs very low communication overhead. Finally, I propose an integrated algorithm and middleware (Ravine Stream) to improve data delivery throughput as well as data persistency in energy-synchronized sensor network

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

Dynamic data-centric storage for long-term storage in wireless sensor and actor networks

Data-Centric Storage (DCS) appears as a novel information storage and delivery mechanism for Wireless Sensor and Actor Networks in which a rendezvous node (home node) is selected to store and serve all the information of a particular application. However, DCS was not designed to provide long-term data availability. In this paper we present a Dynamic DCS solution to enable a long-term storage system. Dynamic DCS proposes to periodically change home nodes over the time based on periods of fixed duration called epochs. This makes it possible to perform temporal queries to previous home nodes in order to retrieve information from the past. We evaluate our proposal using extensive simulations, and reveal that Dynamic DCS makes sensor events available at least 85 % of the maximum lifetime provided by an optimal (but non practical) solution. Finally, we show that Dynamic DCS could easily adapt its storage performance to the requirements of an application by just tuning the epoch duration.The research leading to these results has been partially funded by the Spanish MEC under the CRAMNET project (TEC2012 38362 C03 01) and eeCONTENT Project (TEC2011 29688 C02 02), by the General Directorate of Universities and Research of the Regional Government of Madrid under the ME DIANET Project (S2009/TIC 1468), and by the the INDECT project (Ref 218086) of the 7th EU Framework Programme. In addition, the work of G. de Veciana was supported by the National Science Foundation under Award CNS 0915928.Publicad