QUALITY-DRIVEN CROSS LAYER DESIGN FOR MULTIMEDIA SECURITY OVER RESOURCE CONSTRAINED WIRELESS SENSOR NETWORKS

The strong need for security guarantee, e.g., integrity and authenticity, as well as privacy and confidentiality in wireless multimedia services has driven the development of an emerging research area in low cost Wireless Multimedia Sensor Networks (WMSNs). Unfortunately, those conventional encryption and authentication techniques cannot be applied directly to WMSNs due to inborn challenges such as extremely limited energy, computing and bandwidth resources. This dissertation provides a quality-driven security design and resource allocation framework for WMSNs. The contribution of this dissertation bridges the inter-disciplinary research gap between high layer multimedia signal processing and low layer computer networking. It formulates the generic problem of quality-driven multimedia resource allocation in WMSNs and proposes a cross layer solution. The fundamental methodologies of multimedia selective encryption and stream authentication, and their application to digital image or video compression standards are presented. New multimedia selective encryption and stream authentication schemes are proposed at application layer, which significantly reduces encryption/authentication complexity. In addition, network resource allocation methodologies at low layers are extensively studied. An unequal error protection-based network resource allocation scheme is proposed to achieve the best effort media quality with integrity and energy efficiency guarantee. Performance evaluation results show that this cross layer framework achieves considerable energy-quality-security gain by jointly designing multimedia selective encryption/multimedia stream authentication and communication resource allocation

Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures

Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs

SoftCast: Clean-slate Scalable Wireless Video

Video broadcast and mobile video challenge the conventional wireless design. In broadcast and mobile scenarios the bit rate supported by the channel differs across receivers and varies quickly over time. The conventional design however forces the source to pick a single bit rate and degrades sharply when the channel cannot not support the chosen bit rate. This paper presents SoftCast, a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality. To do so, SoftCast ensures the samples of the digital video signal transmitted on the channel are linearly related to the pixels' luminance. Thus, when channel noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. Hence, a receiver with a good channel (low noise) obtains a high fidelity video, and a receiver with a bad channel (high noise) obtains a low fidelity video. We implement SoftCast using the GNURadio software and the USRP platform. Results from a 20-node testbed show that SoftCast improves the average video quality (i.e., PSNR) across broadcast receivers in our testbed by up to 5.5dB. Even for a single receiver, it eliminates video glitches caused by mobility and increases robustness to packet loss by an order of magnitude

SoftCast

The focus of this demonstration is the performance of streaming video over the mobile wireless channel. We compare two schemes: the standard approach to video which transmits H.264/AVC-encoded stream over 802.11-like PHY, and SoftCast -- a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality

Experimental evaluation of a video streaming system for Wireless Multimedia Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs) are recently emerging as an extension to traditional scalar wireless sensor networks, with the distinctive feature of supporting the acquisition and delivery of multimedia content such as audio, images and video. In this paper, a complete framework is proposed and developed for streaming video flows in WMSNs. Such framework is designed in a cross-layer fashion with three main building blocks: (i) a hybrid DPCM/DCT encoder; (ii) a congestion control mechanism and (iii) a selective priority automatic request mechanism at the MAC layer. The system has been implemented on the IntelMote2 platform operated by TinyOS and thoroughly evaluated through testbed experiments on multi-hop WMSNs. The source code of the whole system is publicly available to enable reproducible research. © 2011 IEEE

AttentionCode: Ultra-Reliable Feedback Codes for Short-Packet Communications

Ultra-reliable short-packet communication is a major challenge in future wireless networks with critical applications. To achieve ultra-reliable communications beyond 99.999%, this paper envisions a new interaction-based communication paradigm that exploits feedback from the receiver. We present AttentionCode, a new class of feedback codes leveraging deep learning (DL) technologies. The underpinnings of AttentionCode are three architectural innovations: AttentionNet, input restructuring, and adaptation to fading channels, accompanied by several training methods, including large-batch training, distributed learning, look-ahead optimizer, training-test signal-to-noise ratio (SNR) mismatch, and curriculum learning. The training methods can potentially be generalized to other wireless communication applications with machine learning. Numerical experiments verify that AttentionCode establishes a new state of the art among all DL-based feedback codes in both additive white Gaussian noise (AWGN) channels and fading channels. In AWGN channels with noiseless feedback, for example, AttentionCode achieves a block error rate (BLER) of $10^{-7}$ when the forward channel SNR is 0 dB for a block size of 50 bits, demonstrating the potential of AttentionCode to provide ultra-reliable short-packet communications.Comment: Ultra-reliable short-packet communications, feedback, deep learning, the attention mechanis

Progressively communicating rich telemetry from autonomous underwater vehicles via relays

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution June 2012As analysis of imagery and environmental data plays a greater role in mission construction and execution, there is an increasing need for autonomous marine vehicles to transmit this data to the surface. Without access to the data acquired by a vehicle, surface operators cannot fully understand the state of the mission. Communicating imagery and high-resolution sensor readings to surface observers remains a significant challenge – as a result, current telemetry from free-roaming autonomous marine vehicles remains limited to ‘heartbeat’ status messages, with minimal scientific data available until after recovery. Increasing the challenge, longdistance communication may require relaying data across multiple acoustic hops between vehicles, yet fixed infrastructure is not always appropriate or possible. In this thesis I present an analysis of the unique considerations facing telemetry systems for free-roaming Autonomous Underwater Vehicles (AUVs) used in exploration. These considerations include high-cost vehicle nodes with persistent storage and significant computation capabilities, combined with human surface operators monitoring each node. I then propose mechanisms for interactive, progressive communication of data across multiple acoustic hops. These mechanisms include wavelet-based embedded coding methods, and a novel image compression scheme based on texture classification and synthesis. The specific characteristics of underwater communication channels, including high latency, intermittent communication, the lack of instantaneous end-to-end connectivity, and a broadcast medium, inform these proposals. Human feedback is incorporated by allowing operators to identify segments of data thatwarrant higher quality refinement, ensuring efficient use of limited throughput. I then analyze the performance of these mechanisms relative to current practices. Finally, I present CAPTURE, a telemetry architecture that builds on this analysis. CAPTURE draws on advances in compression and delay tolerant networking to enable progressive transmission of scientific data, including imagery, across multiple acoustic hops. In concert with a physical layer, CAPTURE provides an endto- end networking solution for communicating science data from autonomous marine vehicles. Automatically selected imagery, sonar, and time-series sensor data are progressively transmitted across multiple hops to surface operators. Human operators can request arbitrarily high-quality refinement of any resource, up to an error-free reconstruction. The components of this system are then demonstrated through three field trials in diverse environments on SeaBED, OceanServer and Bluefin AUVs, each in different software architectures.Thanks to the National Science Foundation, and the National Oceanic and Atmospheric Administration for their funding of my education and this work

Timely and Massive Communication in 6G: Pragmatics, Learning, and Inference

5G has expanded the traditional focus of wireless systems to embrace two new connectivity types: ultra-reliable low latency and massive communication. The technology context at the dawn of 6G is different from the past one for 5G, primarily due to the growing intelligence at the communicating nodes. This has driven the set of relevant communication problems beyond reliable transmission towards semantic and pragmatic communication. This paper puts the evolution of low-latency and massive communication towards 6G in the perspective of these new developments. At first, semantic/pragmatic communication problems are presented by drawing parallels to linguistics. We elaborate upon the relation of semantic communication to the information-theoretic problems of source/channel coding, while generalized real-time communication is put in the context of cyber-physical systems and real-time inference. The evolution of massive access towards massive closed-loop communication is elaborated upon, enabling interactive communication, learning, and cooperation among wireless sensors and actuators.Comment: Submitted for publication to IEEE BITS (revised version preprint

Mobile cloud computing and network function virtualization for 5g systems

The recent growth of the number of smart mobile devices and the emergence of complex multimedia mobile applications have brought new challenges to the design of wireless mobile networks. The envisioned Fifth-Generation (5G) systems are equipped with different technical solutions that can accommodate the increasing demands for high date rate, latency-limited, energy-efficient and reliable mobile communication networks. Mobile Cloud Computing (MCC) is a key technology in 5G systems that enables the offloading of computationally heavy applications, such as for augmented or virtual reality, object recognition, or gaming from mobile devices to cloudlet or cloud servers, which are connected to wireless access points, either directly or through finite-capacity backhaul links. Given the battery-limited nature of mobile devices, mobile cloud computing is deemed to be an important enabler for the provision of such advanced applications. However, computational tasks offloading, and due to the variability of the communication network through which the cloud or cloudlet is accessed, may incur unpredictable energy expenditure or intolerable delay for the communications between mobile devices and the cloud or cloudlet servers. Therefore, the design of a mobile cloud computing system is investigated by jointly optimizing the allocation of radio, computational resources and backhaul resources in both uplink and downlink directions. Moreover, the users selected for cloud offloading need to have an energy consumption that is smaller than the amount required for local computing, which is achieved by means of user scheduling. Motivated by the application-centric drift of 5G systems and the advances in smart devices manufacturing technologies, new brand of mobile applications are developed that are immersive, ubiquitous and highly-collaborative in nature. For example, Augmented Reality (AR) mobile applications have inherent collaborative properties in terms of data collection in the uplink, computing at the cloud, and data delivery in the downlink. Therefore, the optimization of the shared computing and communication resources in MCC not only benefit from the joint allocation of both resources, but also can be more efficiently enhanced by sharing the offloaded data and computations among multiple users. As a result, a resource allocation approach whereby transmitted, received and processed data are shared partially among the users leads to more efficient utilization of the communication and computational resources. As a suggested architecture in 5G systems, MCC decouples the computing functionality from the platform location through the use of software virtualization to allow flexible provisioning of the provided services. Another virtualization-based technology in 5G systems is Network Function Virtualization (NFV) which prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off-the-shelf hardware is less reliable than the dedicated network elements used in conventional cellular deployments. The typical solution for this problem is to duplicate network functions across geographically distributed hardware in order to ensure diversity. For that reason, the development of fault-tolerant virtualization strategies for MCC and NFV is necessary to ensure reliability of the provided services