The emergence of cloud computing has been dramatically changing the landscape of services for modern computer applications. Offloading computation to the cloud effectively expands the usability of mobile terminals beyond their physical limits, and also greatly extends their battery charging intervals through potential energy savings. In this article, we present an overview of computation offloading in mobile cloud computing. We identify the key issues in developing new applications that effectively leverage cloud resources for computation-intensive modules, or migrating such modules in existing applications to the mobile cloud. We then analyze two representative applications in detail from both the macro and micro perspectives, cloud-assisted distributed interactive mobile applications and cloud-assisted motion estimation for mobile video compression, to illustrate the unique challenges, benefit, and implementation of computation offloading in mobile cloud computing. We finally summarize the lessons learned and present potential future avenues.

When mobile terminals meet the cloud: computation offloading as the bridge

Geographic energy-aware non-interfering multipath routing for multimedia transmission in wireless sensor networks

Wireless multimedia sensor networks will play a central role in the Internet of Things world, providing content-rich information for an uncountable number of monitoring and control scenarios. As more applications rely on multimedia data, security concerns gain attention, and new approaches arise to provide security for such networks. However, the usual resource constraints of processing, memory and the energy of multimedia-based sensors have brought different challenges for data encryption, which have driven the development of different security approaches. In this context, this article presents the state-of-the-art of cryptography in wireless multimedia sensor networks, surveying innovative works in this area and discussing promising research directions.

/pdf/cryptography-in-wireless-multimedia-sensor-networks-a-survey-zx9rm559g8.pdf

Cryptography in Wireless Multimedia Sensor Networks: A Survey and Research Directions

Dynamic Measurement Rate Allocation for Distributed Compressive Video Sensing

In wireless communications, sensitive information is frequently exchanged, requiring remote authentication. Remote authentication involves the submission of encrypted information, along with visual and audio cues (facial images/videos, human voice, and so on). Nevertheless, Trojan horse and other attacks can cause serious problems, especially in the cases of remote examinations (in remote studying) or interviewing (for personnel hiring). This paper proposes a robust authentication mechanism based on semantic segmentation, chaotic encryption, and data hiding. Assuming that user X wants to be remotely authenticated, initially X’s video object (VO) is automatically segmented, using a head-and-body detector. Next, one of X’s biometric signals is encrypted by a chaotic cipher. Afterwards, the encrypted signal is inserted to the most significant wavelet coefficients of the VO, using its qualified significant wavelet trees (QSWTs). QSWTs provide both invisibility and significant resistance against lossy transmission and compression, conditions that are typical of wireless networks. Finally, the inverse discrete wavelet transform is applied to provide the stego-object. Experimental results regarding: 1) security merits of the proposed encryption scheme; 2) robustness to steganalytic attacks, to various transmission losses and JPEG compression ratios; and 3) bandwidth efficiency measures indicate the promising performance of the proposed biometrics-based authentication scheme.

Remote Authentication via Biometrics: A Robust Video-Object Steganographic Mechanism Over Wireless Networks

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video coding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video codecs based on emerging video coding paradigms such as distributed video coding and distributed compressive video sensing for multihop WVSNs. The main objective of this work was to provide an insight into the computational (encoding/decoding) complexity, energy consumption, node and network lifetime, processing and memory requirements, and the quality of reconstruction of these video codecs. Based on the findings, this paper also provides some guidelines for the selection of appropriate video codecs for a given WVSN application.

A comparative analysis of video codecs for multihop wireless video sensor networks

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.

/pdf/distributed-video-coding-for-wireless-video-sensor-networks-43bh3x7m4i.pdf

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

Wireless video sensor networks (WVSNs) have drawn significant attention in recent years due to the advent of low-cost miniaturized cameras, which makes it feasible to realize large-scale WVSNs for a variety of applications including security surveillance, environmental tracking, and health monitoring. However, the conventional video encoding paradigms are not suitable for WVSNs due to resource constraints such as limited computation power, battery energy, and network bandwidth. In this paper, we evaluated and analyzed the performance of video encoders based on emerging video encoding paradigms such as distributed video coding (DVC) and distributed compressive video sensing (DCVS) for WVSN. The main objective of this work is to provide an insight about the computational complexity and energy consumption of these video encoders, and the quality of reconstruction from the encoded frames. Based on the findings, this paper also provides some guidelines for the selection of appropriate video encoders for a given WVSN application.

Performance analysis of video encoders for wireless video sensor networks

In this paper, we propose a semi-oblivious energy-aware adaptive watermarking scheme for wireless image sensor networks, which considered key characteristics such as the embedding capacity, security, imperceptibility, computation, and communication energy requirements. We evaluated the distortion in cover image due to watermark redundancies, the number of embedding locations with respect to two channel adaptive parameters, and the impact of compression of cover image on the correctness of extracted watermark. In addition, we investigated the robustness of the scheme against statistical analysis attacks. The results have shown that the proposed scheme has sufficient capacity to embed redundant watermarks in the cover image in an imperceptible manner with reasonably low distortion. The scheme is also considered relatively robust against collusion and middleman attacks.

A semi-oblivious energy-aware adaptive watermarking for wireless image sensor networks

Low complexity video coding that provides efficient compression with reasonable reconstruction quality has been a desired requirement for resource-constrained video sensors in distributed vision-based sensing applications In this paper, we present a review of the state-of-the-art codec architectures based on distributed compressive video sensing (DCVS), which is a relatively new video coding paradigm that integrates the techniques of distributed video coding (DVC) and compressive sensing (CS) The review includes a comparative discussion of several well-known DCVS architectures in literature with a focus on their functional aspects, and suggests a number of possible enhancements to the design of these architectures

http://ieeexplore.ieee.org/iel7/6477876/6484553/06484569.pdf

Noreen Imran

Papers

A comparative analysis of video codecs for multihop wireless video sensor networks

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

Performance analysis of video encoders for wireless video sensor networks

A semi-oblivious energy-aware adaptive watermarking for wireless image sensor networks

Distributed compressive video sensing: A review of the state-of-the-art architectures