Arslan Munir

SIP-Based IMS Signaling Analysis for WiMax-3G Interworking Architectures

The third-generation partnership project (3GPP) and 3GPP2 have standardized the IP multimedia subsystem (IMS) to provide ubiquitous and access network-independent IP-based services for next-generation networks via merging cellular networks and the Internet. The application layer Session Initiation Protocol (SIP), standardized by 3GPP and 3GPP2 for IMS, is responsible for IMS session establishment, management, and transformation. The IEEE 802.16 worldwide interoperability for microwave access (WiMax) promises to provide high data rate broadband wireless access services. In this paper, we propose two novel interworking architectures to integrate WiMax and third-generation (3G) networks. Moreover, we analyze the SIP-based IMS registration and session setup signaling delay for 3G and WiMax networks with specific reference to their interworking architectures. Finally, we explore the effects of different WiMax-3G interworking architectures on the IMS registration and session setup signaling delay.

Multi-Core Embedded Wireless Sensor Networks: Architecture and Applications

Technological advancements in the silicon industry, as predicted by Moores law, have enabled integration of billions of transistors on a single chip. To exploit this high transistor density for high performance, embedded systems are undergoing a transition from single-core to multi-core. Although a majority of embedded wireless sensor networks (EWSNs) consist of single-core embedded sensor nodes, multi-core embedded sensor nodes are envisioned to burgeon in selected application domains that require complex in-network processing of the sensed data. In this paper, we propose an architecture for heterogeneous hierarchical multi-core embedded wireless sensor networks (MCEWSNs) as well as an architecture for multi-core embedded sensor nodes used in MCEWSNs. We elaborate several compute-intensive tasks performed by sensor networks and application domains that would especially benefit from multi-core embedded sensor nodes. This paper also investigates the feasibility of two multi-core architectural paradigms-symmetric multiprocessors (SMPs) and tiled many-core architectures (TMAs)-for MCEWSNs. We compare and analyze the performance of an SMP (an Intel-based SMP) and a TMA (Tileras TILEPro64) based on a parallelized information fusion application for various performance metrics (e.g., runtime, speedup, efficiency, cost, and performance per watt). Results reveal that TMAs exploit data locality effectively and are more suitable for MCEWSN applications that require integer manipulation of sensor data, such as information fusion, and have little or no communication between the parallelized tasks. To demonstrate the practical relevance of MCEWSNs, this paper also discusses several state-of-the-art multi-core embedded sensor node prototypes developed in academia and industry. We further discuss research challenges and future research directions for MCEWSNs.

Markov Modeling of Fault-Tolerant Wireless Sensor Networks

Technological advancements in communications and embedded systems have led to the proliferation of wireless sensor networks (WSNs) in a wide variety of application domains. One commonality across all WSN application domains is the need to meet application requirements (e.g., lifetime, reliability, etc.). Many application domains require that sensor nodes be deployed in harsh environments (e.g., ocean floor, active volcanoes), making these sensor nodes more prone to failures. Unfortunately, sensor node failures can be catastrophic for critical or safety related systems. To improve reliability in such systems, we propose a fault-tolerant sensor node model for applications with high reliability requirements. We develop Markov models for characterizing WSN reliability and MTTF (Mean Time to Failure) to facilitate WSN application-specific design. Results show that our proposed fault-tolerant model can result in as high as a 100% MTTF increase and approximately a 350% improvement in reliability over a non-fault-tolerant WSN. Results also highlight the significance of a robust fault detection algorithm to leverage the benefits of fault-tolerant WSNs.

An MDP-based application oriented optimal policy for wireless sensor networks

Technological advancements due to Moores law have led to the proliferation of complex wireless sensor network (WSN) domains. One commonality across all WSN domains is the need to meet application requirements (i.e. lifetime, responsiveness, etc.) through domain specific sensor node design. Techniques such as sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e. processor voltage and frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN domain diversity, varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very challenging task. In this paper, we propose an automated Markov Decision Process (MDP)-based methodology to prescribe optimal sensor node operation (selection of values for tunable parameters such as processor voltage, processor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more closely meets application requirements compared to other feasible policies.

Modeling and Analysis of Fault Detection and Fault Tolerance in Wireless Sensor Networks

Technological advancements in communications and embedded systems have led to the proliferation of Wireless Sensor Networks (WSNs) in a wide variety of application domains. These application domains include but are not limited to mission-critical (e.g., security, defense, space, satellite) or safety-related (e.g., health care, active volcano monitoring) systems. One commonality across all WSN application domains is the need to meet application requirements (e.g., lifetime, reliability). Many application domains require that sensor nodes be deployed in harsh environments, such as on the ocean floor or in an active volcano, making these nodes more prone to failures. Sensor node failures can be catastrophic for critical or safety-related systems. This article models and analyzes fault detection and fault tolerance in WSNs. To determine the effectiveness and accuracy of fault detection algorithms, we simulate these algorithms using ns-2. We investigate the synergy between fault detection and fault tolerance and use the fault detection algorithms’ accuracies in our modeling of Fault-Tolerant (FT) WSNs. We develop Markov models for characterizing WSN reliability and Mean Time to Failure (MTTF) to facilitate WSN application-specific design. Results obtained from our FT modeling reveal that an FT WSN composed of duplex sensor nodes can result in as high as a 100% MTTF increase and approximately a 350% improvement in reliability over a Non-Fault-Tolerant (NFT) WSN. The article also highlights future research directions for the design and deployment of reliable and trustworthy WSNs.

High-Performance Energy-Efficient Multicore Embedded Computing

With Moores law supplying billions of transistors on-chip, embedded systems are undergoing a transition from single-core to multicore to exploit this high-transistor density for high performance. Embedded systems differ from traditional high-performance supercomputers in that power is a first-order constraint for embedded systems; whereas, performance is the major benchmark for supercomputers. The increase in on-chip transistor density exacerbates power/thermal issues in embedded systems, which necessitates novel hardware/software power/thermal management techniques to meet the ever-increasing high-performance embedded computing demands in an energy-efficient manner. This paper outlines typical requirements of embedded applications and discusses state-of-the-art hardware/software high-performance energy-efficient embedded computing (HPEEC) techniques that help meeting these requirements. We also discuss modern multicore processors that leverage these HPEEC techniques to deliver high performance per watt. Finally, we present design challenges and future research directions for HPEEC system development.

Analysis of SIP-Based IMS Session Establishment Signaling for WiMax-3G Networks

The IP multimedia subsystem (IMS) is standardized by the 3rd generation partnership project (3GPP) and 3GPP2 as a new core network domain to support Internet Protocol (IP) based multimedia services over 3G networks. Session initiation protocol (SIP) which is an application layer signaling protocol is also standardized by 3GPP and 3GPP2 for session establishment, management, and transformation. In this paper, we study the SIP-based signaling delay for IMS session establishment in 3rd generation (3G) network and worldwide interoperability for microwave access (WiMax) network for different channel rates. In our delay analysis, we take into account transmission, processing and queueing delays at network nodes. The delay analysis of SIP based signaling for IMS provides an insight into the efficiency of SIP signaling for IMS.

An MDP-Based Dynamic Optimization Methodology for Wireless Sensor Networks

Wireless sensor networks (WSNs) are distributed systems that have proliferated across diverse application domains (e.g., security/defense, health care, etc.). One commonality across all WSN domains is the need to meet application requirements (i.e., lifetime, responsiveness, etc.) through domain specific sensor node design. Techniques such as sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e., processor voltage and frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN domain diversity, varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very challenging task. In this paper, we propose an automated Markov Decision Process (MDP)-based methodology to prescribe optimal sensor node operation (selection of values for tunable parameters such as processor voltage, processor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more closely meets application requirements compared to other feasible policies.

Vulnerability of Deep Reinforcement Learning to Policy Induction Attacks

Deep learning classifiers are known to be inherently vulnerable to manipulation by intentionally perturbed inputs, named adversarial examples. In this work, we establish that reinforcement learning techniques based on Deep Q-Networks (DQNs) are also vulnerable to adversarial input perturbations, and verify the transferability of adversarial examples across different DQN models. Furthermore, we present a novel class of attacks based on this vulnerability that enable policy manipulation and induction in the learning process of DQNs. We propose an attack mechanism that exploits the transferability of adversarial examples to implement policy induction attacks on DQNs, and demonstrate its efficacy and impact through experimental study of a game-learning scenario.

Interworking architectures for IP multimedia subsystems

The future fourth generation wireless heterogeneous networks aim to integrate various wireless access technologies and to support the IMS (IP multimedia subsystem) sessions. In this paper, we propose the Loosely Coupled Satellite-Cellular-WiMAX-WLAN (LCSCW2) and the Tightly Coupled Satellite- Cellular-WiMAX-WLAN (TCSCW2) interworking architectures. The LCSCW2 and TCSCW2 architectures use the loosely coupling and tightly coupling approach, respectively. Both of them integrate the satellite networks, third generation (3G) wireless networks, worldwide interoperability for microwave access (WiMAX), and wireless local area networks (WLANs). They can support IMS sessions and provide global coverage. The LCSCW2 architecture facilitates independent deployment and traffic engineering of various access networks. The TCSCW2 architecture can provide quality of service (QoS) guarantee. We also propose an analytical model to determine the associate cost for the signaling and data traffic for inter-system communication in these architectures. The cost analysis includes the transmission, processing, and queueing costs at various entities. Numerical results are presented for different arrival rates and session lengths.