H. D. Mustafa

Replicating the geographical cloud

This paper discusses the current state-of-art and proposes a novel evolution of cloud computing and communications. New attributes, introduced continuously, have additively improved and evolved cloud computing to what it is today. Grid computing, data-centers and High Performance Computing (HPC) are critically reviewed and fall-outs are analyzed to corroborate new solutions. We propound a futuristic paradigm, founded on symbiosis and utility-oriented ideas, and propose a new architecture/framework for systems of the future. The authors have also made an attempt to address the question of what is to transcend cloud computing and current networking paradigms. Several applications are discussed qualitatively and rudimentary approaches are discussed. Principal theoretic feasibility of one of the proposed hypothesis of cloud communications is established. In this proposed scenario we obtain a linear increase in communication capacity, with minimal energy requirement. Unified and distributed communication paradigm Green Symbiotic Cloud Communications.Design postulates for technological systems of future.Virtualization and abstraction are introduced creating a true sense geographical cloud.Architecture allows multiple users to access multiple mediums concomitantly.Linear capacity maximization with minimal power utilization is derived and proved.

A novel algorithm for multiple signal classification with Optimized Coulomb Energy Neural Networks for Power line communications

With the advancement in modulation schemes and cognitive techniques, Powerline Communications (PLC), have gained tremendous importance as a medium for transmission of variety of signals. The varied signals when sent through a common channel require a rigorous classification procedure for effective routing at both the transmission and receiving ends. In this paper we present complete software based, low cost, approach for classification of signals sent via the powerline. The algorithm entails structured preprocessing of the received signals, and ensemble them further for effective classification using a novel Optimized Coulomb Energy Neural Network (OCENN). The simulation and experimental results obtained shows an accuracy of more than 97% which is much better than the results of the comparative hardware approaches, which are costly and difficult to implement. It has been noticed in our experimentations that noise and attenuation experienced over the powerline affecting the higher frequency signals does not have an impact on our classification procedure, thus providing a robust architecture for implementation of PLC.

Application of crisp and fuzzy clustering algorithms for identification of hidden patterns from plethysmographic observations on the Radial Pulse

Radial Pulse forms the most basic and essential physical sign in clinical medicine. The paper proposes the application of crisp and fuzzy clustering algorithms under supervised and unsupervised learning scenarios for identifying non-trivial regularities and relationships of the radial pulse patterns obtained by using the Impedance Plethysmographic technique. The objective of our paper is to unearth the hidden patterns to capture the physiological variabilities from the arterial pulse for clinical analysis, thus providing a very useful tool for disease characterization. A variety of fuzzy algorithms including Gustafson-Kessel (GK) and Gath-Geva (GG)have been intensively tested over a diverse group of subjects and over 4855 data sets. Exhaustive testing over the data set show that about 80 % of the patterns are successfully classified thus providing promising results. A Rank Index of 0.7739 is obtained under supervised learning, which provides an excellent conformity of our process with the results of plethysmographic experts. A correlation of the patterns with the diseases of heart, liver and lungs is judiciously performed.

Dual band M-shaped UWB patch antenna for Wireless Body Area Networks

Increased health awareness in people and evolution of wearable computing, has unarguably attracted heightened interest and potential in development of comprehensive and practically feasible Wireless Body Area Networks (WBAN). The paper reports on the full realization of ‘M’ shaped dual band on-body antenna for wireless body area networks operating in the ultra wide band range. The resonant bands are obtained in the frequency range of 5.47 to 5.68 GHz and 6.15 to 6.23 GHz offering a bandwidth of 200 and 80 megahertz respectively. Experimental results of the proposed antenna are demonstrated on universal software radio peripheral kit with a dual, frequency shift keying — frequency modulation. The input impedance, antenna efficiency, directivity, gain and radiation efficiency of the proposed antenna are72 Ω, 64 %, 7.30 dBi, 3.521 dBi and 75 % respectively. Furthermore, the compact size and negligible on body radiation makes it an ideal choice for operation in WBAN environment. Comparison with the existing dual band ‘E’ and ‘V’ shaped antennas vouches a strong candidature for the proposed architecture.

Green symbiotic heterogeneous networks

This paper proposes a symbiotic and distributed communication paradigm for heterogeneous networks. The green and adaptive approach entails the simultaneous use of multiple communication interfaces, enabling efficient resource utilization. The judiciously designed architecture allows multiple users to access multiple mediums concomitantly, for both uplink and downlink, via virtualized communication ports and Internet Protocol (IP) schematic. Principal theoretic feasibility of the hypothesis is established by the linear increase in communication ca-pacity, with minimal energy requirement. Promising simulation and experimental results of a static scenario are shown, User Equipments (UEs) connecting to multiple Communication Mediums (CMs).

A Crowd-Cloud architecture for Big Data analytics

The 3 Vs defining big data raises the need for non-conventional computing and communication architectures for its analytics and processing. In this paper we evolve a new architecture based on amalgamating benefits of Crowdsourcing and Cloud Computing. The “Crowd-Cloud” architecture so formed presents newer domains for efficient analysis and processing of big data. By integrating the sensing and processing capabilities of the mobile dynamic cloud, the “Crowd-Cloud” architecture provides an efficient and increased functionality in handling Big Data. The proposed architecture furthermore has two-fold benefits, minimizing the overall energy consumption and efficiently utilizing the available resources. In the context of energy constraints and dynamic nature of a mobile cloud, a job assignment problem is formulated and an algorithm is proposed to reach a priority based energy efficient solution. Simulations performed over several different scenarios using realistic energy consumption models, applicable for some of the commercially available mobile devices, favors practical implementation of the “Crowd-Cloud” concept.

tuPOY: Epitomizing a New Epoch in Communications With Polymer Textiles

The paper presents a new paradigm from the perspective of pervasive on-body computing through an innovative polymerized textile, which exhibits sensing and radiation properties. A radical, first of its kind, sensor fabricated from unsaturated polymer resin textile, establishes a dynamic link connecting human thermodynamics to electrical ambiance. A dynamic fabrication process of esterification and η-polymerization is developed, which is articulately arrested using an innovatively formulated retardant, yielding a permanent thermally unstable partially oriented yarn (tuPOY). A prudently established nontrivial interchange phenomenon is founded, presenting an inimitable calibration mechanism of the sensors and charting a novel relationship of exuberated energy to lattice kinetics of tuPOY. This meticulously researched conducting medium of tuPOY, fabricated from aromatic polyamides, also presents an avant-garde architecture for proliferation of electrical and thermal signals concomitantly between the sensors and its transmission circuit. A power generating unit (PGU) delineates the power mining from thermal energy dissipated from the body, presenting a new dimension in operational power dynamics. A textile composite antenna is premeditated exclusively from radiating tuPOY-based patch and substrate, an archetype reporting in published literature. The judiciously designed antenna, with tuPOY coupled as its patch, and substrate operate as shields against the radiations directed towards the body leading to a self-sustained sculpt. The back-end hardware of the test setup conceptualizes an automated physician machine (APM) presenting a standalone architecture. The artificial intelligence core of APM is modeled on weighted multiclass support vector machines (wmSVMs). The capturing of signal variations, devoid of any metallic components, presents a singular facet of research and amalgamates various interdisciplinary fields, while providing a robust architecture with minimum tradeoffs.

Non-invasive, reflection coefficient based channel estimation on PLC systems

The major advantage of a PLC system is the unification of the communication architecture into a singular medium. In our efforts towards this unification, we propose a non-invasive, reflection coefficient based channel estimation technique over low voltage powerlines. The novel model accounts for all the parameters of the signal viz., quality, strength, attenuation etc., by simplistic inference from the measured magnetic field intensity. To validate the proposed model experimental results are conducted over real time low voltage PLC architecture. Results of the extensively measured values are compared with its respective actual conditions. We obtain an average accuracy of 97.61 %, 97.49 %, and 97.86 % for the varying frequency, load and voltage profiles, respectively. The proposed model is further compared with three existing PLC models. We attain a mean error of 2.5 % which is lower than all the existing models, thus promising a strong candidature for PLC systems.

Decision Making in Green Symbiotic Cloud Communications

The Green Symbiotic Cloud Communications (GSCC) paradigm created on the concept of cloud communications facilitates the use of multiple communication mediums concomitantly. In this paper, we address the issue of formulating a cognitive decision function based on utility theory, which allows users with GSCC enabled devices to intelligently distribute its bandwidth requirement amongst the available communication mediums. The green and symbiotic approach entails the simultaneous use of multiple communication interfaces, enabling efficient resource utilization. The judiciously designed architecture allows multiple users to access multiple mediums concomitantly, for both uplink and downlink, via virtualized communication ports and Internet Protocol schematic. Design postulates for technological systems of future are proposed and GSCC is evolved using these concepts.

GSCC Universal Modem: Unifying Communications

Unification of varied signal transmission through a cloud structure of communications is one of the major postulates of the GSCC paradigm. Unification yields new possibilities in architecture evolution wherein a single access point can manage communication demands of multiple standards. In this chapter, the authors propose a novel access point (modem design), which allows for one modem to control all types of Communication Mediums (LTE, 3G, Wi-Fi, etc.) effectively delineating a universal communication modem (UCM). Three innovative modules are proposed, which when amalgamated together, result in UCM. Firstly, when different types of signals are sent and received on different mediums, the receiver needs intelligent channel estimation for coupling and decoupling these signals. An intelligent blind channel estimation scheme is proposed for achieving this. Secondly, the received signals of different or the same mediums need to be classified and routed to the appropriate devices. To accomplish, this we propose a novel Optimized Coulomb Energy Neural Network (OCENN) for classification of incoming signals. Finally, an innovative Internet Protocol (IP) based addressing schematic is proposed, which allows bidirectional communications.