Mohamed Eltoweissy

Towards autonomous vehicular clouds

The dawn of the 21st century has seen a growing interest in vehicular networking and its myriad potential applications. The initial view of practitioners and researchers was that radio-equipped vehicles could keep the drivers informed about potential safety risks and increase their awareness of road conditions. The view then expanded to include access to the Internet and associated services. This position paper proposes and promotes a novel and more comprehensive vision namely, that advances in vehicular networks, embedded devices, and cloud computing will enable the formation of autonomous clouds of vehicular computing, communication, sensing, power and physical resources. Hence, we coin the term, Autonomous Vehicular Clouds (AVCs). A key features distinguishing AVCs from conventional cloud computing is that mobile AVC resources can be pooled dynamically to serve authorized users and to enable autonomy in real-time service sharing and management on terrestrial, aerial, or aquatic pathways or theatres of operations. In addition to general-purpose AVCs, we also envision the emergence of specialized AVCs such as mobile analytics laboratories. Furthermore, we envision that the integration of AVCs with ubiquitous smart infrastructures including intelligent transportation systems, smart cities, and smart electric power grids, will have an enormous societal impact enabling ubiquitous utility cyber-physical services at the right place, right time, and with right-sized resources.

Adaptive Fault-Tolerant QoS Control Algorithms for Maximizing System Lifetime of Query-Based Wireless Sensor Networks

Data sensing and retrieval in wireless sensor systems have a widespread application in areas such as security and surveillance monitoring, and command and control in battlefields. In query-based wireless sensor systems, a user would issue a query and expect a response to be returned within the deadline. While the use of fault tolerance mechanisms through redundancy improves query reliability in the presence of unreliable wireless communication and sensor faults, it could cause the energy of the system to be quickly depleted. Therefore, there is an inherent trade-off between query reliability versus energy consumption in query-based wireless sensor systems. In this paper, we develop adaptive fault-tolerant quality of service (QoS) control algorithms based on hop-by-hop data delivery utilizing “source” and “path” redundancy, with the goal to satisfy application QoS requirements while prolonging the lifetime of the sensor system. We develop a mathematical model for the lifetime of the sensor system as a function of system parameters including the “source” and “path” redundancy levels utilized. We discover that there exists optimal “source” and “path” redundancy under which the lifetime of the system is maximized while satisfying application QoS requirements. Numerical data are presented and validated through extensive simulation, with physical interpretations given, to demonstrate the feasibility of our algorithm design.

BioRAC: biologically inspired resilient autonomic cloud

Our modern cyber-powered society will provide pervasive information services that will touch all aspects of our life and economy. However, we are experiencing grand challenges to secure and protect our cyberspace resources and services. The recent embrace of cloud computing due to their performance and cost considerations will further exacerbate the security problem. In cloud computing, organizations relinquish direct control of many security aspects to the service providers such as trust, privacy preservation, identity management, data and software isolation, and service availability. Traditional security techniques will not work well in a cloud environment due to many challenges related to the monoculture paradigm, the rapid and dynamic changes, the use of social networking software tools, and use of mobile devices. In this paper, we present the design of biorac: biologically-inspired resilient autonomic cloud that employs biologically inspired techniques and multi-level tunable redundancy techniques to increase attack and exploitation resilience in cloud computing. We briefly describe how biorac can tolerate and minimize the impact of novel cyber attacks.

ChameleonSoft: Software Behavior Encryption for Moving Target Defense

Ubiquitous cyber systems and their supporting infrastructure impact productivity and quality of life immensely. Their penetration in our daily life increases the need for their enhanced resilience and for means to secure and protect them. One major threat is the contemporary software monoculture. Recent research illustrated the vulnerability of the software monoculture and proposed diversity to reduce the attack surface. In this paper, we propose a biologically-inspired defense system, ChameleonSoft, that employs multidimensional software diversity to, in effect, induce spatiotemporal “software behavior encryption” for moving target defense. The key principles of ChameleonSoft are decoupling functional roles from runtime role players; devising intrinsically-resilient composable online-programmable building blocks; separating logic, state and physical resources; and employing functionally-equivalent, behaviorally-different code variants. ChameleonSoft is also equipped with an autonomic failure recovery mechanism for enhanced resilience. Nodes employing ChameleonSoft autonomously and cooperatively change their recovery and encryption policies both proactively and reactively according to the continual changes in context and environment. Using analysis and simulation, our results show that chameleonsoft can encrypt the execution behavior by confusion and diffusion induction at a reasonable overhead.

Big data and semantics management system for computer networks

We define Big Networks as those that generate big data and can benefit from big data management in their operations. Examples of big networks include the current Internet and the emerging Internet of things and social networks. The ever-increasing scale, complexity and heterogeneity of the Internet make it harder to discover emergent and anomalous behavior in the network traffic. We hypothesize that endowing the otherwise semantically-oblivious Internet with memory management mimicking the human memory functionalities would help advance the Internet capability to learn, conceptualize and effectively and efficiently store traffic data and behavior, and to more accurately predict future events. Inspired by the functionalities of human memory, we proposed a distributed network memory management system, termed NetMem, to efficiently store Internet data and extract and utilize traffic semantics in matching and prediction processes. In particular, we explore Hidden Markov Models (HMM), Latent Dirichlet Allocation (LDA), and simple statistical analysis-based techniques for semantic reasoning in NetMem. Additionally, we propose a hybrid intelligence technique for semantic reasoning integrating LDA and HMM to extract network semantics based on learning patterns and features with syntax and semantic dependencies. We also utilize locality sensitive hashing for reducing dimensionality. Our simulation study using real network traffic demonstrates the benefits of NetMem and highlights the advantages and limitations of the aforementioned techniques.

CORM: A reference model for future computer networks

This paper acknowledges the need for revolutionary designs to devise the Future Internet by presenting a clean-slate Concern-Oriented Reference Model (CORM) for architecting future networks. CORM is derived in accordance to the Function-Behavior-Structure engineering framework, conceiving computer networks as a distributed software-dependent complex system. CORM networks are designed along two main dimensions: a vertical dimension addressing structure and configuration of network building blocks; and a horizontal dimension addressing communication and interaction among the previously formulated building blocks. For each network dimension, CORM factors the design space into function, structure, and behavior, applying to each the principle of separation of concerns for further systematic decomposition. Perceiving the network as a complex system, CORM constructs the network recursively in a bottom-up approach starting by the network building block, whose structure and behavior are inspired by an evolutionary bacterium cell. Hence, CORM is bio-inspired, it refutes the long-endorsed concept of layering, it accounts intrinsically for emergent behavior fostering network integrity and stability. We conjecture that networks designed according to CORM-based architectures can adapt and further evolve to better fit their contexts. To justify our conjecture, we derive and simulate a CORM-based architecture for ad hoc networks.

Associative routing for wireless sensor networks

Traditionally routing in computer networks has focused on finding paths along which data packets could be delivered to pre-identified destination nodes. Most existing routing protocols rely on the use of network addresses as unique node or group identifiers that are usually numeric and independent of any application semantics. The semantically-oblivious identification has forced network designers to incorporate resource/service discovery techniques at higher layers of the network stack, resulting in unnecessary overhead. While such overhead can be tolerated in high-speed wired networks, it significantly limits performance and network lifetime in wireless infrastructure-less networks with battery-powered resource-constrained devices like sensor networks. Moreover, sensor nodes are more naturally anonymous and therefore assigning unique identifiers to individual node limits network scalability and imposes significant overhead on resource management. In this paper, we propose associative routing as a class of routing protocols that enables dynamic semantically-rich descriptive identification of network resources and services. As such, associative routing presents a clear departure from most current network addressing schemes, eliminating the need for a separate phase of resource/service discovery. We hypothesize that since, in essence, resource discovery operates similarly to path discovery then both can be performed in a single phase, leading to significant reduction in traffic load and communication latency without any loss of generality. We also propose a framework for associative routing and present adaptive multi-criteria routing (AMCR) protocol as a realization of associative routing for sensor networks. AMCR exploits application-specific message semantics, represented as generic criteria, and adapts its operation according to observed traffic patterns. Analytical results demonstrate the effectiveness, efficiency, and scalability of AMCR.

Towards trustworthy shared networked sensor-actuator systems

We are witnessing a rapid expansion in the adoption of networked sensor-actuator systems (NSAS) deployed in support of applications such as smart homes, health management, public safety, and emergency management. Many of these emerging applications require large-scale deployment of NSAS and often have dynamic application-specific mission and evolving quality-of-service (QoS) requirements that include timeliness, reliability, security and availability. The shared and federated use of NSAS resources, to achieve multi-application goals, is a key to cost effective NSAS industry. This necessitates the decoupling of the NSAS physical infrastructure from application provisioning, and protecting applications and infrastructure resources from threats. The failure of NSAS nodes, due to malicious or non-malicious conditions, represents a major threat to the turstworthiness of NSAS platforms. Applications should be able to survive individual failures of resource nodes and change their runtime structure while preserving its operational integrity. Furthermore, for sustainable operation, QoS provisioning must be interwoven with energy conservation as a core priority in NSAS platform design. The large-scale of such networks, their heterogeneous node capabilities, their highly dynamic topology, their resource challenged nodes with the subsequent need for node cooperation, and their likelihood of being deployed in inhospitable environments, pose formidable challenges for the construction of trustworthy, shared NSAS platforms. To support the transition of NSAS from a research-only topic to a cost-efficient commercial industry that brings NSAS products and technologies to market, there is a need for a system-aided engineering methodologies and processes that addresses the industrial activities required for the full life-cycle of NSAS applications starting from the initial design to the evolution as requirements or mission change.

Agents in Service-Oriented Wireless Sensor Networks

Advances in Wireless Sensor Networks (WSNs) are fuelling highly distributed wireless sensors organised for increasingly complex tasks. WSNs will soon evolve beyond current data, network, and resource-oriented architectures. Autonomous and collaborative agents provide relevant parallels for more sophisticated tasking. Agent-based systems present a viable architecture for responding to layers of distributed tasking exhibited by WSNs. They map readily to the Service-Oriented WSN (SOWSN) model layers (mission, network, region, sensor, and capability). This paper explores the synergy between WSN and agent technologies to manage growing complexity of future sensor network applications, revealing key parallels that lend themselves to emergent applications.

Reconfigurable Spaces and Places in Smart Built Environments: A Service Centric Approach

A smart built environment (SBE) contains connected, interactive smart objects that have sensing and actuating capabilities. A network of such objects provides an Internet of Things infrastructure that changes the way how SBEs behave and how the inhabitants interact with them. If SBE components, such as walls and furniture pieces, are mobile and controllable, the geometry and interior design of SBE spaces can be changed in response to inhabitants actions and social activities. An added complexity is the mobility of smart objects and their ability to reconfigure. We describe a preliminary work on a service-based framework that includes SBE reconfiguration services. The layered architecture provides access to the reconfigurable smart objects that react to the user activities and behavior. Initial simulation and preliminary findings are included.