Description:
In this paper, we discuss the problems associated with the present contention resolution mechanism of IEEE 802.11 DCF and present a new, dynamic and robust approach to improve it. Our new MAC, using OFDMA in the physical layer, can incorporate multiple concurrent transmissions or receptions in a dynamic manner and can adjust the collision probability based on the traffic load when nodes are endowed with a single half-duplex radio only. Simulation results show that our system improves throughput by up to 40 percent, reduces collision in control messages by up to 80 percent and reduces the average delay for data transmission by up to 20 percent.
Description:
In a decentralized sensor network, localization process relies on the integrity of participating sensors. Existence of malicious beacon nodes in the vicinity of non-beacon nodes affects this process. This paper presents a trilateration-based secure localization technique, which is capable of estimating the location of a sensor with high accuracy so long four neighbouring beacon nodes are benign, irrespective of the number of neighbouring liars and without assuming any trust model. In realistic scenarios of wireless environment where transmitted signals attenuate randomly due to fading, the liar-tolerance level of this attack-resistant technique has to be relaxed accordingly. Superiority of this technique against the state-of-the-art has been established with extensive simulation results in terms of location estimation accuracy and liar-filtering probability.
Description:
Fixed spectrum licensing policies are unsuitable to meet RF spectrum demand by emerging technologies. Spectrum scarcity is hindering the enhancement of current services or deployment of new services operating in RF spectrum. On the contrary, many portions of the licensed spectrum remain unused or underused for significant period of time creating possibility of opportunistic spectrum access without license. Spectrum sensing is practiced in most of the existing opportunistic spectrum access methods. However, these methods consider identical fading or shadowing channels and ignore spatial variation of unlicensed users, hence fail to capture realistic scenario. We introduce an improved cooperative spectrum sensing technique which incorporates non-identical fading and shadowing, and weighs each non-licensee user's contribution appropriately considering the received power and positional displacements of the users. The proposed method demonstrates better detection accuracy and higher spectrum utilization with fewer cooperating users than other existing methods.
Description:
Vibration signals used for abnormality detection in machine health monitoring (MHM) suffer from significant variation with fault severity. This variation causes overlap among the features belonging to different types of faults resulting in severe degradation of fault detection accuracy. This paper identifies a new problem due to severity variant features and proposes a novel adaptive training set and feature selection (ATSFS) scheme based upon the orientation of the test data. In order to build ATSFS and validate its performance, training and testing data are obtained from different severity levels. To capture the non-stationary behavior of vibration signal, robust tools such as wavelet transform (WT) for time-frequency analysis are employed. Simulation studies show that ATSFS attains high classification accuracy even if training and testing data belong to different severity levels.
Description:
Trade-off between energy-efficiency and reliability in wireless sensor networks is application dependent. Without the reliability, the extended lifetime of a network is of limited use. Due to the inherent correlation between reliability and congestion, it is necessary to reduce congestion to improve reliability. Existing congestion control algorithms in wireless sensor networks are reactive. They attempt to reduce the congestion only after its detection. In this paper, we present Location Aided Congestion Aware Routing (LACAR) protocol that proactively avoids congestion formation and improves data delivery success rate in data gathering wireless sensor networks. Location, energy and congestion information of neighbours together with the location information of the base station determine appropriate routes. Simulation results show that LACAR achieves high packet success rate in an energy-efficient way.
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:
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:
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:
The quick market growth and ubiquitous acceptance of VoIP are primarily due to cheap service. VoIP services can be availed in mobile devices at a very low cost by employing IEEE 802.11 to provide last mile coverage. But call capacity is very low in these networks and call jitter occurs if voice quality requirements are not precisely met. We present a VoIP call capacity model for 802.11 networks which considers the most important real world factors like power capture and imperfect channel. Incorporating multiple channels can increase call capacity while multihop network can provide considerably large coverage. Our capacity model incorporates the effects of both multiple channels and multihop networks. We also consider the availability of multiple radio interfaces and conference call scenarios for ubiquitous applications of our model. To ensure voice quality, in addition to contention analysis, we also model the queue considering collision domain at each hop and formulate call capacity by estimating precise impairment budget over multihop.
Description:
Multimedia sensor services and technologies play an important role in seamlessly providing andmanaging health, sports, and other services to anyone, everywhere, and anytime. Media sensors are usually equipped with cameras, microphones, and other devices that produce media content and services. Such services and technologies enable caregivers and related professionals to have immediate access to required information for efficient decision making. Since media sensing technology development is growing, many research opportunities are emerging in a broad spectrum of application domains.
Description:
Multimedia sensor services and technologies play an important role in seamlessly providing andmanaging health, sports, and other services to anyone, everywhere, and anytime. Media sensors are usually equipped with cameras, microphones, and other devices that produce media content and services. Such services and technologies enable caregivers and related professionals to have immediate access to required information for efficient decision making. Since media sensing technology development is growing, many research opportunities are emerging in a broad spectrum of application domains.
Description:
When network resources are shared between Instantaneous Request (IR) and Book-Ahead (BA) connections, activation of future BA connections may cause preemption of on-going IR connections due to resource scarcity. Rerouting of preempted calls via alternative feasible paths is often considered as the final option to restore and maintain service continuity. Existing rerouting techniques, however, do not ensure acceptably low service disruption time and suffer from high failure rate and low network utilization. In this work, a new rerouting strategy is proposed that estimates the future resource scarcity, identifies the probable candidate connections for preemption and initiates the rerouting process in advance for those connections. Simulations on a widely used network topology suggest that the proposed rerouting scheme achieves a higher successful rerouting rate with lower service disruption time, while not compromising other network performance metrics like utilization and call blocking rate.
Description:
The Internet of Things (IoT) has the potential to transform communities around the globe into smart cities. The massive deployment of sensor-embedded devices in the smart cities generates voluminous amounts of data that need to be stored and processed in an efficient manner. Long-haul data transmission to the remote cloud data centers leads to higher delay and bandwidth consumption. In smart cities, the delay-sensitive applications have stringent requirements in term of response time. To reduce latency and bandwidth consumption, edge computing plays a pivotal role. The resource-constrained smart devices at the network core need to offload computationally complex tasks to the edge devices located in their vicinity and have relatively higher resources. In this paper, we propose an end-to-end encryption framework, SmartEdge, for a smart city application by executing computationally complex tasks at the network edge and cloud data centers. Using a lightweight symmetric encryption technique, we establish a secure connection among the smart core devices for multimedia streaming towards the registered and verified edge devices. Upon receiving the data, the edge devices encrypts the multimedia streams, encodes them, and broadcast to the cloud data centers. Prior to the broadcasting, each edge device establishes a secured connection with a data center that relies on the combination of symmetric and asymmetric encryption techniques. In SmartEdge, the execution of a lightweight encryption technique at the resource-constrained smart devices, and relatively complex encryption techniques at the network edge and cloud data centers reduce the resource utilization of the entire network. The proposed framework reduces the response time, security overhead, computational and communication costs, and has a lower end-to-end encryption delay for participating entities. Moreover, the proposed scheme is highly resilient against various adversarial attacks.
Description:
One of the challenging aspects for wireless sensor network (WSN) clustering is to estimate the optimal cluster number. Most WSN clustering techniques have used an a priori value to determine the cluster number. A few techniques, available at the literature, attempted to find the optimal cluster number by energy minimization. However, due to the assumption of lossless communication, these initiatives do not always converge to the minimum energy as wireless channels are error-prone. As wireless communication is always vulnerable to the signal interference, environmental noise, and so on, it suffers from data loss. To capture the characteristics of the communication phenomenon in a real context and have better reliability, we need to embed the link quality into the cluster number determination process. To address this issue, in this paper together with the energy, we incorporate link quality metric into the theoretical underpinning to achieve an optimal cluster number analytically and finally justified the result by simulation.
Description:
This paper presents a canonical dual approach for solving nonconvex minimization problems in Euclidean distance geometry. The variant of this problem arises extensively in engineering and science, including computational biology, sensor network communications, database analysis, information technology, and global optimization. Due to the nonconvexity, most of these problems are NP-hard and traditional convex optimization methods can not be used directly for finding global optimal solutions. We first show that this type of nonconvex problems can be transferred to a concave maximization problem over a convex set. Then a general analytical solution is proposed by using the canonical duality theory. Applications are illustrated by network localization and minimization of Rosenbrock function. Furthermore, by using a perturbed canonical dual approach, a class of Euclidean distance problems can be converted to a unified concave maximization dual problem with zero duality gap, which can be solved by well-developed convex minimization methods.