Kashif Sharif

A Hybrid Anycast Routing Protocol for Load Balancing in Heterogeneous Access Networks

The wireless multihop to an access point model appears to be a promising component of future network architectures, including multihop cellular networks and wireless access networks at the edges of mesh networks. Sophisticated software radios and core network protocols are being developed to support the integration of heterogeneous access networks. A challenge is managing diverse resources at access points (e.g., 3G, WiFi or WiMax), as well as the distributed interference among the mobiles within a heterogeneous access network. We propose the use of a new anycasting protocol to guide access point discovery and path selection for balancing access point resource and routing packets to access points (APs). In addition, a hybrid proactive/reactive approach is used to reduce overhead of AP discovery. We use theoretical analysis and extensive simulations, to study the tradeoff of our hybrid anycasting protocol. The simulation study indicates that the use of the hybrid anycasting protocol for AP discovery, load balancing and routing, results in consistent performance improvements.

Multiple-Metric Hybrid Routing Protocol for Heterogeneous Wireless Access Networks

The wireless multihop to an access point model appears to be a promising component of future network architectures, including multihop cellular networks and wireless access networks at the edges of mesh networks. Sophisticated software radios and core network protocols are being developed to support the integration of heterogeneous air interfaces within these access networks. A key challenge is managing diverse resources at access points (e.g., 3G, WiFi or WiMax) while discovering efficient multi-hop paths from a source to an access point based on selection criteria specified by various applications or necessitated by network resource constraints. We propose a new routing protocol that integrates multiple metrics to calculate path cost based on diverse selection criteria. In addition, a hybrid proactive/reactive anycast routing paradigm is applied to guide the discovery of an access point among multiple available access points. The result is an integrated, flexible protocol for route discovery and access point discovery. Simulation analysis shows that our approach outperforms single-metric routing protocols while supporting flexible service criteria, including load balancing at access points.

Multiple-metric hybrid anycast protocol for heterogeneous access networks

The wireless multihop to an Access Point (AP) model appears to be a promising component of future access network architectures. A key challenge is managing diverse resources at APs while discovering efficient multi-hop paths from source to AP based on selection criteria dictated by applications or necessitated by network constraints. We propose a new hybrid proactive/reactive anycast routing protocol that integrates multiple-metrics to calculate path cost and selects the appropriate AP. Simulation analysis shows that our approach outperforms single-metric protocols while supporting flexible service criteria, including load balancing at APs.

Anycast Based Lightweight Routing Protocol for Mobile Sink Discovery in Sensor Networks

Applications for wireless sensor networks have grown enormously over the past few years. Routing and sink discovery protocols designed for ad hoc networks do not adapt to sensor networks, and generic sensor network routing techniques are not optimnl for all scenarios. We propose a light weight routing prot04:01 to discover mobile sinks in battlefield operations or large terrains. Initial experimentation shows promising results in reduction of control over bead, good data delivery with support of multi-metric path selection.

Multi-layer-based opportunistic data collection in mobile crowdsourcing networks

Along with the explosive popularity of wireless mobile devices and availability of high data rates, new crowdsourcing paradigms have emerged to leverage the power of problem-solving by crowds. A crucial challenge in crowdsourcing is data collection. With the increasing number of mobile users, device to device communication with opportunistic connections has become a real possibility, reducing the load on infrastructure based networks. Crowdsourcing over such opportunistic links presents with unique challenges. This paper proposes to exploit opportunistic transmission to collect data in crowdsourced networks, by using multiple layers of social graphs along with weight training for energy efficient data collection. We design two types of multi-layer-based opportunistic data collection methods by using different dimensions of data. Simulation experiments show that using these techniques, delivery ratio can be increased while reducing the load and energy consumption of the mobile network.

A payload-dependent packet rearranging covert channel for mobile VoIP traffic

Abstract VoIP (Voice over Internet Protocol) is one of the most prevalent services for the mobile users. An enormous amount of audio and video data is transmitted over VoIP communication continuously, to make it potentially available for stealth message transfer. The existing covert channel schemes focus on modifying packet payload or inter-packet delays, the former kind is easy to be detected since a minor modification may lead to distinct abnormalities, while the latter is too sensitive to network jitter due to its short inter-packet delays. Hence, to effectively construct covert channel becomes a challenge, and requires investigation in using mobile VoIP traffic for robust and stealthy covert communication. In this paper, we propose a covert channel scheme which communicates by rearranging the packet sending sequences while keeps the undetectability and robustness. Unlike the existed packet rearranging covert channels which may concentrate on packet rearranging according to the existed packet features such as packet id and packet length, the proposed scheme focuses on building packet rearranging covert channel whose function is regardless of the variation on legitimate traffic. According to the hash value of the payload, the packets are classified into delimiter packets and carrier packets, and the covert message is embedded onto a number of carrier packets (NoCP) between the relative delimiter packets. Moreover, to mitigate the interference from channel noise, the differences between two correlative NoCPs are utilized as the codewords by redundantly partitioning their values into 1-bit symbols. The channel parameters are adjustable to trade off between the efficiency and security. The corresponding experiments are conducted over three kinds of typical mobile VoIP traffics to evaluate the undetectability, robustness and throughput of our scheme. Results of the BER (bit error rate) and KS (Kolmogorov-Smirnov) test show that the scheme is robust and stealthy.

Mo-sleep: Unobtrusive sleep and movement monitoring via Wi-Fi signal

Sleep monitoring system helps to diagnose various health problems. Traditional solutions for sleep monitoring are usually invasive or limited to medical facilities. Radio Frequency (RF) based methods require specialized devices or dedicated wireless sensors. Recently, Wi-Fi based methods without any wearable or dedicated devices obtain more attention, however, they all assume that all the users are in a relatively quiet environment without moving targets. In this paper, we develop a system called Mo-Sleep, which adopts off-the-shelf Wi-Fi devices to continuously collect fine-grained wireless Channel State Information (CSI) in a room. We introduce a motion detection module in our system to identify whether the CSI information has been interfered by a moving target. We then use Principal Component Analysis (PCA) to obtain accurate breath signal. Our prototypic system demonstrates that the proposed scheme can not only remove interfered CSI, but also obtain real time breath rate every five seconds.

Quadrant-Based Weighted Centroid Algorithm for Localization in Underground Mines

Location sensing in wireless sensor networks (WSNs) is a critical problem when it comes to rescue operation in underground mines. Most of the existing research on node localization uses traditional centroid algorithm-based approach. However, such approaches have higher localization error, which leads to inaccurate node precision. This paper proposes a novel quadrant-based solution on weighted centroid algorithm that uses received signal strength indicator for range calculation and distance improvement by incorporating alternating path loss factor according to the mine environment. It also makes use of four beacon nodes instead of traditional three with weights applied to reflect the impact of each node for the centroid position. The weight factor applied is the inverse of the distance estimated. Simulation results show higher localization accuracy and precision as compared to traditional weighted centroid algorithms.

SUAA: A Secure User Authentication Scheme with Anonymity for the Single & Multi-server Environments

Abstract The rapid increase in user base and technological penetration has enabled the use of a wide range of devices and applications. The services are rendered to these devices from single-server or highly distributed server environments, irrespective of their location. As the information exchanged between servers and clients is private, numerous forms of attacks can be launched to compromise it. To ensure the security, privacy, and availability of the services, different authentication schemes have been proposed for both single-server and multi-server environments. The primary performance objective of such schemes is to prevent most (if not all) attacks, with minimal computational costs at the server and user ends. To address this challenge, this paper presents a secure user authentication scheme with anonymity (SUAA) for single-server and multi-server environments. It works on 3-factor authentication, involving passwords, smart cards, and biometric data. We use symmetric and asymmetric encryption for single-server and multi-server architectures respectively, to reduce the computational costs. Through a comprehensive security analysis, we show that the proposed scheme is reliable through mutual authentication, and is resilient to attacks addressed by state of the art solutions. Time cost analysis also shows less time required to complete the authentication process.

M2HAV: A Standardized ICN Naming Scheme for Wireless Devices in Internet of Things

The concept Internet of Things in recent years has enabled the connectivity of almost every electronic device using wireless medium, to the Internet. This has created a massive surge in number of heterogeneous wireless devices, with many new challenges regarding content and service naming. The traditional IP-based architectures are now moving towards information/content centric networks. In this paper, we propose a multilayer multi-component hierarchical attribute-value naming scheme for wireless devices. It combines self-certifying names to achieve a standardized naming scheme, which is scalable, efficient, routable, and is secure by design. We use variable-length encoding method to represent hierarchical location names with prefix-labeling. It is highly expressive and customizable using a tree representation, where each level represents a semantic functionality. The qualitative and quantitative analysis show that the proposed scheme is inherently better than many of the available information-centric networking architectures, and is able to reduce the memory and time consumption for name lookup and routing purposes.