Improve Image Decoding in Lightweight Environment Using a Coroutines Based Approach

The JPEG2000 still image compression standard, while providing a remedy for the many shortcomings of its predecessor JPEG, is still slow to establish itself on the Internet. This problem is mainly due to the complexity of the COder-DECoder (CODEC) which implies its non-adoption by large firms and platforms in the field of image acquisition, processing and transmission. Indeed, the encoding and decoding process consumes a lot of CPU, memory and energy resources and takes a lot of computing time. The objective of this paper is to propose a model for decoding jpeg2000 on lightweight devices running on the Android mobile operating system. This implementation uses coroutines, which are a lightweight process model with reduced resource consumption costs compared to conventional AsyncTask threadsets. The model minimizes decoding time while minimizing CPU and memory usage, resulting in a fast and energetically economical decoded image. The results of integrating the coroutines from the main thread into the decoding process instead of the AsyncTask from the main thread produced better performance in terms of computation time, CPU and memory utilization. Indeed, the use of our model has led to a gain of around 23.41% in execution time, 9.8% in CPU utilization rate and 18.56% in memory utilization rate, compared to the model proposed in the literature which uses the threads.

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.

Full Image Inference Conditionally upon Available Pieces Transmitted into Limited Resources Context

In a context marked by the proliferation of smartphones and multimedia applications, the processing and transmission of images have become a real problem. Image compression is the first approach to address this problem, it nevertheless suffers from its inability to adapt to the dynamics of limited environments, consisting mainly of mobile equipment and wireless networks. In this work, we propose a stochastic model to gradually estimate an image upon information on its pixels that are transmitted progressively. We consider this transmission as a dynamical process, where the sender pushes the data in decreasing significance order. In order to adapt to network conditions and performances, instead of truncating the pixels, we suggest a new method called Fast Reconstruction Method by Kalman Filtering (FRM-KF) consisting of recursive inference of the not yet received layers belonging to a sequence of bitplanes. After empirical analysis, we estimate parameters of our model which is a linear discrete Kalman Filter. We assume the initial law of information to be the uniform distribution on the set [0, 255] corresponding to the range of gray levels. The performances of FRM-KF method have been evaluated in terms of the ratios in the quality of data image/size sent and in the quality of image/time required for treatment. A high quality was reached faster with relatively small data (less than 10% of image data is needed to obtain up to the sixth-quality image). The time for treatment also decreases faster with number of received layers. However, we found that the time of image treatment might be large starting from a image resolution of 1024 * 1024. Hence, we recommend FRM-KF method for resolutions less or equal to 512 * 512. A statistical comparative analysis reveals that FRM-KF is competitive and suitable to be implemented on limited resource environments.

Rural Wireless Mesh Network: A Design Methodology

Wireless Mesh Network is presented as an appealing solution for bridging the digital divide between developed and under-developed regions. But the planning and deployment of these networks are not just a technical matter, since the success depends on many other factors tied to the related region. Although we observe some deployments, to ensure usefulness and sustainability, there is still a need of concrete design process model and proper network planning approach for rural regions, especially in Sub-Saharan Africa. This paper presents a design methodology to provide network connectivity from a landline node in a rural region at very low cost. We propose a methodology composed of ten steps, starting by a deep analysis of the region in order to identify relevant constraints and useful applications to sustain local activities and communication. Approach for planning the physical architecture of the network is based on an indoor-outdoor deployment for reducing the overall cost of the network.