Description:
Wireless ad hoc networks are self-configurable distributed systems. One of the major problems in traditional wireless ad hoc networks is interference. The interference could be reduced using smart directional antennas. In this study, multibeam smart antennas have been used. When using this type of antenna, two nodes can communicate when both the sending and receiving beams are pointing towards each other. Also, a node can only communicate with a subset of nodes in its neighborhood depending on the number of beams and their beamwidth. Thus, the network topology needs to be dynamic in this case, and by controlling the topology network, performance can be increased. In this paper, we present a framework of a cross layer approach of topology control that interacts with the routing layer and MAC layer and meets the required QoS of different data streams. The approach is fully distributed. When the network is initialized, the algorithm builds an initial connected topology and the routing algorithm uses this topology to find paths for the current communications. Then, depending on the network scenario, current communications and the required QoS, the topology control layer changes the topology to optimize the network performance. This study concerns suburban ad hoc networks (SAHN) where nodes tend to be fixed and are aware of their locations.
Description:
Decentralized content sharing (DCS) is emerging as a suitable platform for smart mobile device users to generate and share contents seamlessly without the requirement of a centralized server. This feature is particularly important for places that lack Internet coverage such as tourist attractions where users can form an ad-hoc network and communicate opportunistically to share contents. Existing DCS approaches when applied for such type of places suffer from low delivery success rate and high latency. Although a handful of recent approaches have specifically targeted improvement of content delivery service in tourist spot like scenario, these and other DCS approaches do not focus on contents’ demand and supply which vary considerably due to visitor in-and-out flow and occurrence of influencing events. This is further compounded by the lack of any content distribution (replication) scheme. The content delivery service will be improved if contents can be proactively distributed in strategic positions based on dynamic demand and supply and medium access contention. In this paper, we propose a dynamic content distribution scheme (DCDS) considering these practical issues for sharing contents in tourist attractions. Simulation results show that the proposed approach significantly improves (7
Description:
Decentralized content sharing (DCS) is emerging as a suitable platform for smart mobile device users to generate and share contents seamlessly without the requirement of a centralized server. This feature is particularly important for places that lack Internet coverage such as tourist attractions where users can form an ad-hoc network and communicate opportunistically to share contents. Existing DCS approaches when applied for such type of places suffer from low delivery success rate and high latency. Although a handful of recent approaches have specifically targeted improvement of content delivery service in tourist spot like scenario, these and other DCS approaches do not focus on contents’ demand and supply which vary considerably due to visitor in-and-out flow and occurrence of influencing events. This is further compounded by the lack of any content distribution (replication) scheme. The content delivery service will be improved if contents can be proactively distributed in strategic positions based on dynamic demand and supply and medium access contention. In this paper, we propose a dynamic content distribution scheme (DCDS) considering these practical issues for sharing contents in tourist attractions. Simulation results show that the proposed approach significantly improves (7
Description:
Soft handoff in WCDMA systems allows multi connection between the user and base stations during handoff, in contrast to single connection in hard handoff. But multi connection flexibility leads to a trade-off between quality of service for the user and the system downlink capacity. The heterogeneous wireless networks consist of WCDMA and WLAN systems, which operate at different frequency with no direct interference. Therefore, a vertical soft handoff between downlink shared channels from WCDMA and WLAN will not suffer similar side effects as the horizontal soft handoff in WCDMA systems. In this paper, we present an analytical framework for vertical soft handoff and propose a context-aware vertical soft handoff algorithm (CAVSH) for heterogeneous wireless networks. CAVSH considers four user and system context parameters such as user required bandwidth, user traffic cost, access network utilization, and signal to interference-and-noise ratio (SINR). The results show that the proposed CAVSH can provide the system with lower dropping probability, lower average cost to the user and higher throughput, as compared with vertical hard handoff.
Description:
Most existing data models and transmission policies for sensor network assume uniform periodic data generation and unconstrained transmission range for sensor nodes, both assumptions being too restrictive to capture and analyze real- world operation for practical deployment. In this paper, we consider these two practical aspects and present a new transmission policy formulated after (i) stochastic data model where a set of events occur with certain probabilities and rate of data generation by a sensor varies based on sensed event and (ii) limited transmission range of sensors. Assuming co-centric rings around the base station, located at a generic location (internal or external to the network area), ring thickness and hope sizes over lifetime is determined by formatting an optimization problem where nodes in each ring may transmit data at different hop sizes at a given instant and also vary hop sizes over lifetime. Performance analysis shows significant improvement in network lifetime and better uniformity in energy usage distribution in the proposed policy irrespective of network size and maximum allowable transmission range of nodes.
Description:
The 3D Morphable models of the human face have prepared myriad of applications in computer vision, human computer interaction and security surveillances. However, due to the variation in size, complexity of training data set, the landmark mapping, the representation in real time and rendering or synthesis of images in three dimensional is limited. In this paper, we extend the approach of the photometric stereo and provide the human face reconstruction in three dimensional. The proposed method consists of two steps. First it automatically detects the face and segment the iris along with statistical features of pupil location in it. Secondly it provides the selection of minimum six features and where iris process to generate the 3D face. In compare with existing methods our approach provides the automation which produces more better and efficient results in contrast to the manual methods.
Description:
The 3D Morphable models of the human face have prepared myriad of applications in computer vision, human computer interaction and security surveillances. However, due to the variation in size, complexity of training data set, the landmark mapping, the representation in real time and rendering or synthesis of images in three dimensional is limited. In this paper, we extend the approach of the photometric stereo and provide the human face reconstruction in three dimensional. The proposed method consists of two steps. First it automatically detects the face and segment the iris along with statistical features of pupil location in it. Secondly it provides the selection of minimum six features and where iris process to generate the 3D face. In compare with existing methods our approach provides the automation which produces more better and efficient results in contrast to the manual methods.
Description:
For many applications, simultaneous sensing of a number of parameters is crucial that leads to the deployment of multiple classes of sensors having different initial energy, data generation rate and deployment density within the vicinity of a cluster as opposed to identical sensors assumed in the existing heterogeneous sensor networks. For data transmission to cluster head, such networks use single hop, multi hop and their hybrid as intra-cluster transmission policy which suffer highly from non-uniform energy usage among sensors, thereby reducing the lifetime drastically leaving considerable amount of energy in many nodes. In this paper, we propose a framework for multi-class heterogeneous sensor networks where incoming traffic is relayed towards cluster head in collaboration among multiple classes of sensors considering their heterogeneity. We also propose two transmission policies for this framework considering generic polygonal cluster and limited transmission range for individual sensors. Performance analysis shows substantial improvement of overall lifetime by the collaborative framework of multi-class sensors. Our proposed transmission policies further improve the lifetime over existing multi hop and hybrid communications through better distribution of energy usage among sensors.kam
Description:
Two basic legal models have evolved to tackle the problem of unlawful P2P distribution: safe harbour and graduated response. This article will discuss the two models, with a focus on the American safe harbour regime and the French graduated response regime. Also considered is the open question of what will occur in Australia in the aftermath of the High Court's denial of ISP liability in Roadshow Films v iiNet.
Description:
Recently, street furniture, including bins, seats, and bus shelters, has become smart as it has been equipped with environmental sensors, wireless modules, processors, and microcontrollers. Accordingly, smart furniture is expected to become a vital part of the IoT infrastructure and one of the drivers of future smart cities. This work focuses on how smart street furniture can be exploited within the IoT architecture as a basis of recommender systems, toward achieving smart cities' different components. We present and discuss recent relevant work as well as the key challenges and opportunities for future research. We explain that much work is still required when it comes to combining scalability, real-time processing, smart furniture, and recommender systems.
Description:
Funding details: Australian Research Council, ARC Funding text 1: Joarder Kamruzzaman received the BSc and MSc degrees in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Dhaka, and the PhD degree in Information Systems Engineering from Muroran Institute of Technology, Hokkaido, Japan. He is currently a Professor in the School of Science, Engineering and Information Technology, Federation University Australia. Previously, he served as the Director of the Centre for Multimedia Computing, Communications and Artificial Intelligence Research hosted first by Monash University and later by Federation University. His research interests include distributed computing, Internet of Things, machine learning and cyber security. He has published 260+ peer-reviewed publications which include over 80 journal papers, 170 conferences, 11 book chapters and two edited reference books. He is the recipient of Best Paper award in four international conferences: ICICS′15, Singapore; APCC′14, Thailand; IEEE WCNC′10, Sydney, Australia and in the IEEE-ICNNSP′03, Nanjing, China. He has received nearly A$2.3m competitive research funding, including prestigious ARC (Australian Research Council) grant and large CRC (Collaborative Research Centre) grant. He was the founding Program co-Chair of the first International Symposium on Dependability in Sensor, Cloud, and Big Data Systems and Applications (DependSys), China in 2015. He has served 32 conferences in leadership capacities including Program co-Chair, Publicity Chair, Track Chair and Session Chairs, and since 2012 as an Editor of the Elsevier Journal of Network and Computer Applications, and had served as the lead Guest of Elsevier Journal Future Generation Computer Systems.
Description:
In event localization, wireless sensors try to locate the source of an event from its emitted power. This is more challenging than sensor localization as the power level at the source of an event is neither predictable with precision nor can be controlled. Considering the emerging trend of long sensing range for cost-effective sensor deployment, locating events within a region much smaller than the sensing area of a single sensor has gained research interest. This paper proposes the first range-free event localization framework, which avoids expensive hardware needed by the range-based counterparts. Our approach first develops a sensing range model from the statistical information on the emitted power of a type of events so that user-defined event-detection quality can be provisioned using a minimal network of static sensors. Then an accurate event location boundary estimation technique is developed from the sensing feedbacks, which also facilitates guided expansion of the area of possible event location (APEL) to deal with sensing errors. Finally, user-defined event-localization quality guarantee is provisioned cost-effectively by inviting mobile sensors on-demand to target positions. Analytical solutions are provided whenever appropriate and comprehensive simulations are carried out to evaluate localization performance. The proposed event localization technique outperforms the state-of-the-art range-based counterpart (Xu et al., 2011) in realistic environment with path loss, shadow fading, and sensor positioning errors.
Description:
Predictive coding schemes, proposed in the literature, essentially model the residuals with discrete distributions. However, real-valued residuals can arise in predictive coding, for example, from the usage of an r order linear predictor specified by r real-valued coefficients. In this paper, we propose a symbol-by-symbol coding scheme for the Laplace distribution, which closely models the distribution of real-valued residuals in practice. To efficiently exploit the real-valued predictions at a given precision, the proposed scheme essentially combines the process of residual computation and coding, in contrast to conventional schemes that separate these two processes. In the context of adaptive predictive coding framework, where the source statistics must be learnt from the data, the proposed scheme has the advantage of lower 'model cost' as it involves learning only one parameter. In this paper, we also analyze the proposed parametric coding scheme to establish the relationship between the optimal value of the coding parameter and the scale parameter of the Laplace distribution. Our experimental results demonstrated the compression efficiency and computational simplicity of the proposed scheme in adaptive coding of residuals against the widely used arithmetic coding, Rice-Golomb coding, and the Merhav-Seroussi-Weinberger scheme adopted in JPEG-LS.
Description:
Although transmission policy is crucial in extending lifetime of sensor networks, most existing policies make simplified assumptions which include: i) circular cluster with cluster head (CH) at the center, ii) uniform periodic data generation model and iii) unrestricted transmission range for nodes. But, in practice, these assumptions are too restrictive for real-world deployment of heterogeneous sensor networks where clusters are usually polygonal. Moreover, in multi hop transmission energy consumption by sensors varies greatly with their distance from CH and even among sensors in the critical ring due to non-uniform relay traffic caused by asymmetric polygonal structure of cluster. In this paper, we propose a new transmission policy where sensors transmit at optimally determined hop sizes that varies over lifetime and a distributed hop selection algorithm that regulates each packet's arrival to CH within a given hop limit. Our formulation considers generic polygonal cluster, stochastic data generation model where data generation rate by sensors vary with events and limited transmission range for sensors. Performance analysis shows significant improvement in lifetime and better uniformity in energy usage among sensors in the proposed policy irrespective of cluster size, hop limit and maximum allowable transmission range of nodes
Description:
Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
Description:
Blockchain technologies recently emerging for eHealth, can facilitate a secure, decentral- ized and patient-driven, record management system. However, Blockchain technologies cannot accommodate the storage of data generated from IoT devices in remote patient management (RPM) settings as this application requires a fast consensus mechanism, care- ful management of keys and enhanced protocols for privacy. In this paper, we propose a Blockchain leveraged decentralized eHealth architecture which comprises three layers: (1) The Sensing layer –Body Area Sensor Networks include medical sensors typically on or in a patient body transmitting data to a smartphone. (2) The NEAR processing layer –Edge Networks consist of devices at one hop from data sensing IoT devices. (3) The FAR pro- cessing layer –Core Networks comprise Cloud or other high computing servers). A Patient Agent (PA) software replicated on the three layers processes medical data to ensure reli- able, secure and private communication. The PA executes a lightweight Blockchain consen- sus mechanism and utilizes a Blockchain leveraged task-offloading algorithm to ensure pa- tient’s privacy while outsourcing tasks. Performance analysis of the decentralized eHealth architecture has been conducted to demonstrate the feasibility of the system in the pro- cessing and storage of RPM data.
Description:
In predictive coding of integers real-valued residuals are mapped to integers before encoding, leaving room for improvement by reducing the loss due to rounding. In this paper, we propose a new prefix coding scheme where actual integer values, instead of the residuals, are encoded using cosets with real domain predictions as the side information. This novel coding scheme outperforms Golomb-based coding by reducing the rounding loss with similar computational and memory complexity.
Description:
Contention window based medium access protocols are of practical interest in low data rate wireless communication scenarios. In periodic data collection applications, nodes mostly produce small data packets that are collected by the cluster heads and routed to the base station. In this paper, a new mechanism for adaptively selecting the size of the contention window based on the number of contending nodes has been presented. The proposed scheme effectively reduces the number of collisions in periodic collection scenarios with fixed number of nodes. Theoretical analysis and simulation results demonstrate that, in periodic data collection processes, the new protocol reduces the data collection time significantly as compared to IEEE 802.11 and the recently proposed Synchronized Shared Contention Window (SSCW) based scheme.