Bandwidth Conservation Research Articles

Edge Computing: Opportunities and Challenges

Edge computing has emerged as an innovative paradigm, promising to reshape the landscape of computational processing by bringing data closer to the source of generation, namely Internet of Things (IoT) devices. As the proliferation of IoT devices surges, so does the need for efficient, low-latency processing. Edge computing addresses these demands by decentralizing computational tasks, optimizing bandwidth, and ensuring rapid data processing. This paper delves into the nuances of edge computing, highlighting its distinct advantages, particularly in latency reduction and bandwidth conservation. However, with these opportunities come challenges, notably in the domain of security. Through a systematic review and simulation-based experimentation, this research affirms the transformative potential of edge computing, while also underscoring the need for robust security frameworks. The study concludes with a forward-looking perspective, emphasizing areas of future research including security enhancements, integration with 5G technology, energy-efficient architectures, and cross-domain applications.

Edge AI and IoT: Direct integration for on-the-device data processing

The integration of Artificial Intelligence (AI) with the Internet of Things (IoT) devices has led to the emergence of Edge AI, a transformative solution that enables data processing directly on the IoT devices or "at the edge" of the network. This paper explores the benefits of Edge AI, emphasizing reduced latency, bandwidth conservation, enhanced privacy, and faster decision-making. Despite its advantages, challenges like resource constraints on IoT devices persist. By examining the practical implications of Edge AI in sectors like healthcare and urban development, this study underscores the paradigm shift towards more efficient, secure, and responsive technological ecosystems.

Adaptive Lossy Data Compression Extended Architecture for Memory Bandwidth Conservation in SpMV

Adaptive Lossy Data Compression Extended Architecture for Memory Bandwidth Conservation in SpMV

Prototype for Multimedia Content Delivery based on Non-Transmittable Codewords Enhanced Viterbi Algorithm

The paper provides a prototype for multimedia content delivery with reduced channel code rate from conventional Non-Transmittable Codewords Enhanced Viterbi Algorithm. The code rate reduction was simulated using VB.NET Viterbi simulator available at College of Informatics and Virtual Education-University of Dodoma. The study approximates Uplink and downlink speeds limits of the prototype using High Speed Packet Access Evolved technology by assuming all other parameters remain constant. The uplink and downlink of the prototype is clearly presented. The code rate of 1/3 was obtained by simulating different 8-bits patterns. This code rate of 1/3 enabled reduction of encoder output bits from 48-bits to 24-bits, therefore, few bits would be sent to the network and bandwidth conservation is attained. This makes the prototype to be the good choice for low network bandwidth channel. In addition, the reduced code rate will reduce the expenses of user internet bundles, because number of MBs to be charged will be smaller. This prototype for multimedia delivery over network has three benefits, high data transmission reliability due to adopted NTC Enhanced Viterbi, minimum network bandwidth utilization and satisfied uplink and downlink access speed.

Optical wireless communication using camera and RGB display

In this paper, a theoretical framework for Optical Wireless Communication using RGB color model with computer monitor display and digital camera is proposed. The motivation is to find a cheaper alternative to physical network switches and wired and optical cables in communication networks that can be leveraged for computer clusters, thus reducing time and costs for purchase, setup, maintenance, power consumption and cooling. Also, providing better data transfer rates, scalability and band width conservation. The framework is distinguished from related work by the use of RGB for data encoding at various bit-depths. Greater data transfer rates than existing Optical Wireless Communication systems are possible. A computer monitor displays a grid of changing colors controlled by a transmitting host. The color in a grid cell represents one or more data bits as per the RGB codes used. The RGB codes can be computed by logically partitioning the RGB cube, a geometrical representation of the RGB model. A camera on a receiving host, samples the colors to obtain the data bits. Mathematical expressions are derived to compute the RGB codes and mappings to data bits. The upper bound of the data rate is derived and compared with the well-known Shannon communication theorem. The framework is extended to include an array of digital cameras for parallel data copy in a computer cluster and the data rate is determined. Theoretically, the data rate can increase beyond the Gigabit/second realm, and into Terabit/second realm.

Mobile Edge Cloud System: Architectures, Challenges, and Approaches

Mobile edge cloud (MEC) is a model for enabling on-demand elastic access to, or an interaction with a shared pool of reconfigurable computing resources such as servers, storage, peer devices, applications, and services, at the edge of the wireless network in close proximity to mobile users. It overcomes some obstacles of traditional central clouds by offering wireless network information and local context awareness as well as low latency and bandwidth conservation. This paper presents a comprehensive survey of MEC systems, including the concept, architectures, and technical enablers. First, the MEC applications are explored and classified based on different criteria, the service models and deployment scenarios are reviewed and categorized, and the factors influencing the MEC system design are discussed. Then, the architectures and designs of MEC systems are surveyed, and the technical issues, existing solutions, and approaches are presented. The open challenges and future research directions of MEC are further discussed.

Joint Coding-Transmission Optimization for a Video Surveillance System With Multiple Cameras

Surveillance video has become an important multi-media application in recent years, with development trends toward wide viewing angles and high definition. At the same time, transmission of surveillance video over the Internet and storage in the cloud are becoming increasingly popular. However, it is extremely challenging to transfer surveillance video with both a wide viewing angle and a high resolution over the Internet because of 1) the tradeoff between a wide viewing angle and high-surveillance object resolution for a single camera, 2) the large throughput requirement, and 3) the fluctuating delay and bandwidth of the Internet. In this paper, we present a reference-frame-cache-based surveillance video transmission system (RSVTS), which delivers wide-viewing-angle and high-definition surveillance video over the Internet in real time using multiple rotatable cameras. First, we develop an efficient video mosaicing method for merging two (or more) surveillance videos together. Second, novel reference frame selection and update algorithms are proposed for the RSVTS encoder to reduce the amount of encoded data. Third, we implement a reference frame cache on both the sender and receiver sides to increase video quality by increasing the probability of video decoding. We conduct a performance evaluation using a simulation system that integrates RSVTS and ns-3. Compared with the H.264/SVC and H.264/AVC schemes, RSVTS achieves appreciable improvements in enhancing the video peak signal-to-noise ratio and bandwidth conservation.

Envisioning Internet of Things using Fog Computing

Internet of Things is the future of the Internet. It encircles a wide scope. There are currently billions of devices connected to the Internet and this trend is expecting to grow exponentially. Cisco predicts there are at present 20 billion connected devices. These devices, along with their varied data types, transmission rates and communication protocols connect to the Internet seamlessly. The futuristic implementation of Internet of Things across various scenarios demands the real time performance delivery. These range from RFID connected devices to huge data centers. Until date, there is no single communication protocol available for envisioning IoT. There is still no common, agreed upon architecture. Hence, huge challenges lie ahead. One of the ways to envision Internet of Things is to make use of Fog Networks. Fog is essentially a cloudlet, located nearer to the ground. It offers lower latency and better bandwidth conservation. The Fog or Fog computing is a recent concept. The OpenFog Consortium is a joint effort of many vendors. Its latest work is the background study for realizing Fog as a possible paltform for activating Internet of Things. This paper revolves around Envisioning Internet of Things using Fog computing. It begins with a detailed background study of Internet of Things and Fog Architecture. It covers applications and scenarios where such knowledge is highly applicable. The paper concludes by proposing Fog Computing as a possible platform for Internet of Things.

Content-Aware Concurrent Multipath Transfer for High-Definition Video Streaming over Heterogeneous Wireless Networks

Delivering high-definition (HD) wireless video under stringent delay constraint is challenging with regard to the limited network resources and high transmission rate. Concurrent multipath transfer (CMT) using stream control transmission protocol (SCTP) exploits the multihoming feature of mobile devices to establish associations with different access networks. In this paper, we study the multihomed HD video communication with SCTP over heterogeneous wireless networks. The existing CMT schemes mainly treat the traffic data in a content-agnostic fashion, and thus cannot effectively leverage the scarce wireless resources to maximize the perceived video quality. To address this critical issue, we propose a content-aware CMT (CMT-CA) solution that featured by the unequal frame-level scheduling based on estimated video parameters and feedback channel status. First, we develop an analytical framework to model the total distortion of parallel video transmission over multiple wireless access networks. Second, we introduce a joint congestion control and data distribution scheme to minimize the total distortion based on online quality evaluation and Markov decision process (MDP). The performance of CMT-CA is evaluated through extensive semi-physical emulations in Exata involving HD video encoded with H.264 codec. Experimental results show that CMT-CA outperforms the reference schemes in terms of video peak signal-to-noise ratio (PSNR), end-to-end delay, and goodput. Or conversely, CMT-CA achieves the same video quality with $20$ percent bandwidth conservation.

Delay-Constrained High Definition Video Transmission in Heterogeneous Wireless Networks with Multi-Homed Terminals

Delivering high-quality mobile video with the limited radio resources is challenging due to the time-varying channel status and stringent Quality of Service (QoS) requirements. Multi-homing support enables mobile terminals to establish multiple simultaneous associations for enhancing transmission performance. In this paper, we study the multi-homed communication of delay-constrained High Definition (HD) video in heterogeneous wireless networks. The low-delay encoded HD video streaming consists exclusively of Intra (I) and Predicted (P) frames. In the capacity-limited wireless networks, it is highly possible the large-size I frames experience deadline violations and induce severe quality degradations. To address the challenging problem, we propose a novel scheduling framework dubbed del A y S tringent CO ded T ransmission (ASCOT) that featured by frame-level data protection and allocation over multiple wireless access networks . First, we perform online video distortion estimation to simulate multi-homed transmission impairments according to the feedback channel status and input video data. Second, we control the frame protection level by adapting the Forward Error Correction (FEC) coding redundancy and video data allocation to achieve target quality. The performance of the proposed ASCOT is evaluated through semi-physical emulations in Exata using real-time H.264 video streaming. Experimental results show that ASCOT outperforms existing transmission schemes in improving the video PSNR (Peak Signal-to-Noise Ratio), reducing the end-to-end delay, and increasing the goodput. Or conversely, ASCOT achieves the same video quality with approximately $20$ percent bandwidth conservation .

Buffer-aided device-to-device communication: opportunities and challenges

To meet the increasing demands for popular content downloading services in next-generation cellular networks, device-to-device (D2D) communication was proposed to enable user equipments (UEs) to communicate directly over the D2D links in addition to traditional cellular operation by base stations (BSs), which is capable of utilizing the available cellular network’s resource more efficiently to enhance content downloading performance. Although buffer-aided protocols may provide significant throughput gains in wireless networks, the opportunities and challenges of buffer-aided D2D communications are not yet fully understood. Differing from most existing works that focus on investigating buffering policy, we analyze the fundamental impact of the constrained buffers on the D2D communication underlaying cellular system by an optimization framework. Our study quantitatively reveals the positive correlation between the buffer sizes of BSs and UEs and the overall system performance, as well as further revealing the opportunities created by buffer-aided D2D communications for bandwidth conservation. In addition, we discuss practical challenges inherent in buffer-limited D2D communication underlaying next generation cellular networks, including increased transmission delay and optimal bandwidth allocation.

MELOC-X: extended memory and location optimized caching for large mobile ad hoc networks of UAVs

Effective caching in mobile ad hoc network increases data availability. However, caching at strategic locations with reduced (controlled) number of copies is needed for many military applications involving UAVs to address security concerns, less maintenance overhead and maintaining availability. In general, existing cooperative caching approaches are deficient in finding the reduced number of strategic cache locations. One such technique to reduce the number of strategic cache locations without affecting the efficacy of data access for a small network topology of UAVs is called "memory and location optimized caching scheme (MELOC)". However, having a single broker and metadata broadcast across the whole network in MELOC lead to severe performance hindrance in case of a large network topology of UAVs. Moreover, frequent cache replacements due to a change in network topology do not favor cache hit and bandwidth conservation in case of large mobile networks consisting of UAVs. In this paper, we design and evaluate an extended version of "MELOC called MELOC-X", which suits large network topologies of UAVs by overcoming the above challenges. Our comparison with one such recent scheme with similar objectives showcased a significant improvement in performance. We also evaluate the impact of this scheme with respect to different metrics including the average number of hops, the average roundtrip time (i.e., average query latency), cache hits and mobility to access cached data through extensive simulations.

Overlay construction for mobile peer-to-peer video broadcasting

An efficient overlay is a crucial component of wireless cooperative live video streaming networks—an emerging wireless streaming solution with ever-increasing storage and computation capabilities, and provides scalability, autonomy, carrier-billing network bandwidth conservation, service coverage extension, etc. Based on whether routes are pre-calculated and maintained, or determined per-hop in reactive to each data piece, the streaming overlay can be classified as either unstructured, structured, or hybrid. We discuss issues, properties and example approaches of each category in detail, and present quantitative and qualitative comparisons on their strengths and weaknesses in terms of system robustness, overlay maintenance complexity, delivery ratio, end-to-end delay, etc. Finally we discuss some open issues and emerging areas regarding overlay construction.

A Survey on Multicast Routing Protocols for Mobile Ad Hoc Networks

There are many benefits of multicasting using with network. The communication cost reduced by multicasting for applications that sends the same data to many recipients instead of sending via multiple unicast. This paper gives a general survey of multicast routing protocols in Mobile adhoc Networks (MANETs). The multicast routing protocols are divided into two categories- multicast routing based on application independence and multicast routing based on application dependence. Multicast routing protocols plays an important role in MANETs to provide group communication. Multicasting is one of the major communication technologies primarily designed for bandwidth conservation and an efficient way of transferring data to a group of receivers in wireless mesh networks.

Enhancement of Image Compression in Neural Network Using Wavelets

Image compression is the technique of reducing the size of image file without degrading the quality of the image Bandwidth conservation is an important issue in case of multimedia communication. Uncompressed multimedia (graphical, audio and video) data requires considerable storage capacity and transmission bandwidth. It demands for data storage capacity and data-transmission bandwidth continuously to outstrip the capabilities of available technologies. So to solve this problem an efficient multimedia communication scheme is proposed which is based on Wavelet. This paper shows the idea of image compression based on hierarchical back propagation neural network and results are analyzed The further analysis is conducted in the network model and tested training algorithm. This concludes that a high compression ratio is achieved with Bi-orthogonal Wavelet functions. The results are obtained with a Bi-orthogonal 6.8 Reconstruction Wavelet function and proved the best. Then Neural Network is implemented to prove the best result and hence achieved. Experimental results suggest that the proposed system can be efficiently used to compress while maintaining high image compression.

A performance comparison of CDA and ICDA in ADRP

Broadcasting is an inevitable operation in networks. This paper addresses the issues related to broadcasting such as node interference and latency delay in ad-hoc networks .These problems could be overcome by our proposed algorithm approximate directional routing protocol (ADRP) which is mainly inspired by the existing on-demand directional routing protocol (DRP). DRP is also similar to Dynamic Source Routing (DSR). The use of directional antennas for broadcasting is gaining acceptance in ad-hoc networks. The key benefits of smart antennas are minimum energy consumption and bandwidth conservation. Although excess of literature is directed toward the use of smart antennas, a powerful protocol for reducing redundancy, end-to-end delay, and interference is being researched. One such protocol is ADRP. ADRP is a reactive protocol that combines the effect of DRP and approximation algorithm that finds optimal solution for broadcast problems. Omni-directional antennas are capable of wide angle signal transmission. Compared with omni-directional antennas, its successor directional antennas have come up with significant advantages of reducing packet redundancy and interference by gaining higher signal-to-noise ratio. The duo pack will considerably decrease end-to-end delay and node interference giving out significant performance benefits thereby substantially increasing throughput.

A Secure Mobile Payment Framework in MANET Environment

In this paper the authors propose a Secure Mobile Payment Framework in Multi hop Cellular Network environment (which is an integration of cellular networks and mobile ad hoc networks) using Mobile Agent technology and Digital Signature with Message Recovery (DSMR) mechanism based on ECDSA mechanism. Secure communication in Multi hop Cellular Networks is a nontrivial task because of lack of infrastructure, no prior trust relationships among nodes due to the absence of a centralized authority. Mobile Agent technology and Digital Signature with Message Recovery based on ECDSA mechanism provides secure mobile payments in Multi hop Cellular Networks. Mobile Agent technology has many benefits such as bandwidth conservation, reduction of latency, reduction of completion time, Asynchronous (disconnected) communications. Digital Signature with Message Recovery based on ECDSA eliminates the need of adopting PKI cryptosystems. The proposed protocol ensures Authentication, Integrity, Confidentiality and Non Repudiation, achieves Identity protection from merchant and Eavesdropper, achieves Transaction privacy from Eavesdropper and Payment Gateway, achieves Payment Secrecy, Order Secrecy, forward secrecy, prevents Double Spending, Overspending and Money laundering. The security properties of the proposed protocol have been verified successfully using BAN Logic, AVISPA and Scyther Tools and presented with results.

Filter Augmented JPEG Algorithms: A Critical Performance Study for Improving Bandwidth

recent years, use of Digital Image Communication has increased exponentially in the day to day activities. Joint Photographic Experts Group (JPEG) is the most widely used still image compression standard for bandwidth conservation. In this paper, it is proposed and critically studied a new set of JPEG Compression algorithms by combining Mean filtering, Median filtering, and Outlier detection algorithms and conventional JPEG DCT algorithm in a staged manner. This outlier based JPEG algorithm is giving exceptionally compression compared to conventional JPEG algorithm. Experiments are carried out with many standard still images. Algorithms developed in this paper, identified to be giving almost same Peak Signal-to-Noise Ratio (PSNR) as that of standard JPEG algorithm.

Development of Low Bit Rate Speech Encoder based on Vector Quantization and Compressive Sensing

Speech coding is a representation of a digitized speech signal using as few bits as possible, while maintaining reasonable level of speech quality. Due to growing need for bandwidth conservation in wireless communication, the research in speech coding has increased. Recently, Compressive Sensing (CS) is gaining a great interest because of its ability to recover original signals by taking only few measurements. CS is a new approach that goes against the common data acquisition methods. In this research, a new system of speech encoding system is developed using compressive sensing. Since CS performs well in sparse signals, different sparsifying transforms are analyzed and compared using Gini coefficient. The quality of the speech coder is evaluated using Perceptual Evaluation of Speech Quality (PESQ), Signal-to-Noise Ratio (SNR) and subjective listening tests. Results show that the speech coders have achieved a PESQ score of 3.16 at 4 kbps which is a good quality as confirmed by listening tests. Furthermore, the coder is also compared with Code Excited Linear Prediction (CELP) coder.

Data Replication in Cooperative Mobile Ad-Hoc Networks

The mobile computing environment provides many benefits such as ubiquitous access to computing but includes constraints on resources such as available bandwidth and battery life. Replication is a widely recognized method for balancing the demands of storage space with bandwidth and battery life. We propose a novel scheme that seeks to strategically balance these constrained resources through a cooperative game-theory approach for replication in a mobile environment. Our replication strategy relies on the cooperation of the nodes within the network to make replica caching decisions which are spatiotemporally local-optimal for the network from an energy and bandwidth conservation standpoint. In cooperative altruistic data replication, each node calculates the net global benefit, for caching a replica of the requested data, as the result data is returned from the responding node to the requesting node, where it determines the spatiotemporally local-optimal node for replicating the data item. Performance results from our research indicate that our scheme, CADR, improves the query response time by 25 and 45 %, mean hop count is improved by 26 and 46 %, query error is reduced by 30 and 48 %, while energy utilization is reduced 30 and 57 % when compared with both another game theoretic replication approach and standard cooperative caching respectively.