Biblio

Connectivity is at the heart of the future Internet-of-Things (IoT) infrastructure, which can control and communicate with remote sensors and actuators for the beacons, data collections, and forwarding nodes. Existing sensor network solutions cannot solve the bottleneck problems near the sink node; the tree-based Internet architecture has the single point of failure. To solve current deficiencies in multi-hop mesh network and cross-domain network design, we propose a mesh inside a mesh IoT network architecture. Our designed "edge router" incorporates these two mesh networks together and performs seamlessly transmission of multi-standard packets. The proposed IoT testbed interoperates with existing multi-standards (Wi-Fi, 6LoWPAN) and segments of networks, and provides both high-throughput Internet and resilient sensor coverage throughout the community.

In this demonstration, we showcase the XD middleware, a framework for expressive multiplexing of application communication streams onto underlying device-to-device communication links. XD allows applications to remain agnostic about which low-level networking stack is actually delivering messages and instead focus on the application-level content and delivery parameters. The IoT space has been flooded with new communication technologies (e.g., BLE, ZigBee, 6LoWPAN) to add to those already available on modern mobile devices (e.g., BLE, WiFi-Direct), substantially increasing the barrier to entry for developing innovative IoT applications. XD presents application developers with a simple publish-subscribe API for sending and receiving data streams, unburdening them from the task of selecting and coordinating communication channels. Our demonstration shows two Android applications, Disseminate and Prophet, running using our XD middleware for communication. We implemented BLE, WiFi Direct with TCP, and WiFi Direct with UDP communication stacks underneath XD.

The specification and implementation of network protocols are difficult tasks. This is particularly the case for WSN nodes which are typically implemented on low power microcontrollers with limited processing capabilities. Those platforms do not have the resources to run a full-fledged operating system but instead are programmed using a Real Time Operating System (RTOS) specialized in low-power wireless communications. The most popular are Contiki and TinyOS. Those RTOS support a fully-compliant IPv6 stack including the 6LoWPAN adaptation layer [1], several radio duty-cycling MAC protocols [2], [3] and multiple routing protocols [4].

In order to integrate equipment from different vendors, wireless sensor networks need to become more standardized. Using IP as the basis of low power radio networks, together with application layer standards designed for this purpose is one way forward. This research focuses on implementing and deploying a system using Contiki, 6LoWPAN over an 868 MHz radio network, together with CoAP as a standard application layer protocol. A system was deployed in the Cairngorm mountains in Scotland as an environmental sensor network, measuring streams, temperature profiles in peat and periglacial features. It was found that RPL provided an effective routing algorithm, and that the use of UDP packets with CoAP proved to be an energy efficient application layer. This combination of technologies can be very effective in large area sensor networks.

Standard routing protocols for IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) are mainly designed for data collection applications and work by establishing a tree-based network topology, which enables packets to be sent upwards, from the leaves to the root, adapting to dynamics of low-power communication links. The routing tables in such unidirectional networks are very simple and small since each node just needs to maintain the address of its parent in the tree, providing the best-quality route at every moment. In this work, we propose Matrix, a platform-independent routing protocol that utilizes the existing tree structure of the network to enable reliable and efficient any-to-any data traffic. Matrix uses hierarchical IPv6 address assignment in order to optimize routing table size, while preserving bidirectional routing. Moreover, it uses a local broadcast mechanism to forward messages to the right subtree when persistent node or link failures occur. We implemented Matrix on TinyOS and evaluated its performance both analytically and through simulations on TOSSIM. Our results show that the proposed protocol is superior to available protocols for 6LoWPAN, when it comes to any-to-any data communication, in terms of reliability, message efficiency, and memory footprint.

How to get two Raspberry Pis to communicate over a 6LoWPAN network.

Internet Engineering Task Force (IETF) is working on 6LoW-PAN standard which allows smart devices to be connected to Internet using large address space of IPV6. 6LoWPAN acts as a bridge between resource constrained devices and the Internet. The entire IoT space is vulnerable to local threats as well as the threats from the Internet. Due to the random deployment of the network nodes and the absence of tamper resistant shield, the resource constrained IoT elements face potential insider attacks even in presence of front line defense mechanism that involved cryptographic protocols. To detect such insidious nodes, an Intrusion Detection System (IDS) is required as a second line of defense. In this paper, we attempt to analyze such potential insider attacks, while reviewing the IDS based countermeasures. We attempt to propose a baseline for designing IDS for 6LoWPAN based IoT system.

IoT applications will rely on the connections between sensors and actuators and the internet. This will likely be wireless, and it will have to be low power.

Usage patterns of mobile devices depend on a variety of factors such as time, location, and previous actions. Hence, context-awareness can be the key to make mobile systems to become personalized and situation dependent in managing their resources. We first reveal new findings from our own Android user experiment: (i) the launching probabilities of applications follow Zipf's law, and (ii) inter-running and running times of applications conform to log-normal distributions. We also find context-dependency in application usage patterns, for which we classify contexts in a personalized manner with unsupervised learning methods. Using the knowledge acquired, we develop a novel context-aware application scheduling framework, CAS that adaptively unloads and preloads background applications in a timely manner. Our trace-driven simulations with 96 user traces demonstrate the benefits of CAS over existing algorithms. We also verify the practicality of CAS by implementing it on the Android platform.

With limited battery supply, power is a scarce commodity in wireless sensor networks. Thus, to prolong the lifetime of the network, it is imperative that the sensor resources are managed effectively. This task is particularly challenging in heterogeneous sensor networks for which decisions and compromises regarding sensing strategies are to be made under time and resource constraints. In such networks, a sensor has to reason about its current state to take actions that are deemed appropriate with respect to its mission, its energy reserve, and the survivability of the overall network. Sensor Management controls and coordinates the use of the sensory suites in a manner that maximizes the success rate of the system in achieving its missions. This article focuses on formulating and developing an autonomous energy-aware sensor management system that strives to achieve network objectives while maximizing its lifetime. A team-theoretic formulation based on the Belief-Desire-Intention (BDI) model and the Joint Intention theory is proposed as a mechanism for effective and energy-aware collaborative decision-making. The proposed system models the collective behavior of the sensor nodes using the Joint Intention theory to enhance sensors’ collaboration and success rate. Moreover, the BDI modeling of the sensor operation and reasoning allows a sensor node to adapt to the environment dynamics, situation-criticality level, and availability of its own resources. The simulation scenario selected in this work is the surveillance of the Waterloo International Airport. Various experiments are conducted to investigate the effect of varying the network size, number of threats, threat agility, environment dynamism, as well as tracking quality and energy consumption, on the performance of the proposed system. The experimental results demonstrate the merits of the proposed approach compared to the state-of-the-art centralized approach adapted from Atia et al. [2011] and the localized approach in Hilal and Basir [2015] in terms of energy consumption, adaptability, and network lifetime. The results show that the proposed approach has 12 × less energy consumption than that of the popular centralized approach.

This paper proposes a taxonomy of autonomous vehicle handover situations with a particular emphasis on situational awareness. It focuses on a number of research challenges such as: legal responsibility, the situational awareness level of the driver and the vehicle, the knowledge the vehicle must have of the driver's driving skills as well as the in-vehicle context. The taxonomy acts as a starting point for researchers and practitioners to frame the discussion on this complex problem.

We propose PADA, a new power evaluation tool to measure and optimize power use of mobile sensing applications. Our motivational study with 53 professional developers shows they face huge challenges in meeting power requirements. The key challenges are from the significant time and effort for repetitive power measurements since the power use of sensing applications needs to be evaluated under various real-world usage scenarios and sensing parameters. PADA enables developers to obtain enriched power information under diverse usage scenarios in development environments without deploying and testing applications on real phones in real-life situations. We conducted two user studies with 19 developers to evaluate the usability of PADA. We show that developers benefit from using PADA in the implementation and power tuning of mobile sensing applications.

In international military coalitions, situation awareness is achieved by gathering critical intel from different authorities. Authorities want to retain control over their data, as they are sensitive by nature, and, thus, usually employ their own authorization solutions to regulate access to them. In this paper, we highlight that harmonizing authorization solutions at the coalition level raises many challenges. We demonstrate how we address authorization challenges in the context of a scenario defined by military experts using a prototype implementation of SAFAX, an XACML-based architectural framework tailored to the development of authorization services for distributed systems.

We propose a new security paradigm that makes cross-layer personalization a premier component in the design of security solutions for computer infrastructure and situational awareness. This paradigm is based on the observation that computer systems have a personalized usage profile that depends on the user and his activities. Further, it spans the various layers of abstraction that make up a computer system, as if the user embedded his own DNA into the computer system. To realize such a paradigm, we discuss the design of a comprehensive and cross-layer profiling approach, which can be adopted to boost the effectiveness of various security solutions, e.g., malware detection, insider attacker prevention and continuous authentication. The current state-of-the-art in computer infrastructure defense solutions focuses on one layer of operation with deployments coming in a "one size fits all" format, without taking into account the unique way people use their computers. The key novelty of our proposal is the cross-layer personalization, where we derive the distinguishable behaviors from the intelligence of three layers of abstraction. First, we combine intelligence from: a) the user layer, (e.g., mouse click patterns); b) the operating system layer; c) the network layer. Second, we develop cross-layer personalized profiles for system usage. We will limit our scope to companies and organizations, where computers are used in a more routine and one-on-one style, before we expand our research to personally owned computers. Our preliminary results show that just the time accesses in user web logs are already sufficient to distinguish users from each other,with users of the same demographics showing similarities in their profiles. Our goal is to challenge today's paradigm for anomaly detection that seems to follow a monoculture and treat each layer in isolation. We also discuss deployment, performance overhead, and privacy issues raised by our paradigm.

Recent advances in vehicle automation have led to excitement and discourse in academia, industry, the media, and the public. Human factors such as trust and user experience are critical in terms of safety and customer acceptance. One of the main challenges in partial and conditional automation is related to drivers' situational awareness, or a lack thereof. In this paper, we critically analyse state of the art implementations in this arena and present a proactive approach to increasing situational awareness. We propose to make use of augmented reality to carefully design applications aimed at constructs such as amplification and voluntary attention. Finally, we showcase an example application, Pokémon DRIVE, that illustrates the utility of our proposed approach.

Research towards my dissertation has involved a series of perceptual and accessibility-focused studies concerned with the use of tactile cues for spatial and situational awareness, displayed through head-mounted wearables. These studies were informed by an initial participatory design study of mobile technology multitasking and tactile interaction habits. This research has yielded a number of actionable conclusions regarding the development of tactile interfaces for the head, and endeavors to provide greater insight into the design of advanced tactile alerting for contextual and spatial understanding in assistive applications (e.g. for individuals who are blind or those encountering situational impairments), as well as guidance for developers regarding assessment of interaction between under-utilized sensory modalities and underlying perceptual and cognitive processes.

This paper describes the challenges of converting the classic Pac-Man arcade game into a virtual reality game. Arcaid provides players with the tools to maintain sufficient situation awareness in an environment where, unlike the classic game, they do not have full view of the game state. We also illustrate methods that can be used to reduce a player's simulation sickness by providing visual focal points for players and designing user interface elements that do not disrupt immersion.

Opportunistic Situation Identification (OSI) is new paradigms for situation-aware systems, in which contexts for situation identification are sensed through sensors that happen to be available rather than pre-deployed and application-specific ones. OSI extends the application usage scale and reduces system costs. However, designing and implementing OSI module of situation-aware systems encounters several challenges, including the uncertainty of context availability, vulnerable network connectivity and privacy threat. This paper proposes a novel middleware framework to tackle such challenges, and its intuition is that it facilitates performing the situation reasoning locally on a smartphone without needing to rely on the cloud, thus reducing the dependency on the network and being more privacy-preserving. To realize such intuitions, we propose a hybrid learning approach to maximize the reasoning accuracy using limited phone's storage space, with the combination of two the-state-the-art techniques. Specifically, this paper provides a genetic algorithm based optimization approach to determine which pre-computed models will be selected for storage under the storage constraints. Validation of the approach based on an open dataset indicates that the proposed approach achieves higher accuracy with comparatively small storage cost. Further, the proposed utility function for model selection performs better than three baseline utility functions.

Named Data Networking (NDN), a clean-slate data oriented Internet architecture targeting on replacing IP, brings many potential benefits for content distribution. Real deployment of NDN is crucial to verify this new architecture and promote academic research, but work in this field is at an early stage. Due to the fundamental design paradigm difference between NDN and IP, Deploying NDN as IP overlay causes high overhead and inefficient transmission, typically in streaming applications. Aiming at achieving efficient NDN streaming distribution, this paper proposes a transitional architecture of NDN/IP hybrid network dubbed Centaur, which embodies both NDN's smartness, scalability and IP's transmission efficiency and deployment feasibility. In Centaur, the upper NDN module acts as the smart head while the lower IP module functions as the powerful feet. The head is intelligent in content retrieval and self-control, while the IP feet are able to transport large amount of media data faster than that if NDN directly overlaying on IP. To evaluate the performance of our proposal, we implement a real streaming prototype in ndnSIM and compare it with both NDN-Hippo and P2P under various experiment scenarios. The result shows that Centaur can achieve better load balance with lower overhead, which is close to the performance that ideal NDN can achieve. All of these validate that our proposal is a promising choice for the incremental and compatible deployment of NDN.

Increase in M2M use cases, the availability of narrow band spectrum with operators and a need for very low cost modems for M2M applications has led to the discussions around what is called as Cellular IOT (CIOT). In order to develop the Cellular IOT network, discussions are focused around developing a new air interface that can leverage narrow band spectrum as well as lead to low cost modems which can be embedded into M2M/IOT devices. One key issue that arises during the development of a clean slate CIOT network is that of coexistence with the 4G networks. In this paper we explore architectures for Cellular IOT and 4G network harmonization that also addresses the one key requirement of possibly using narrow channels for IOT on the existing 4G networks and not just as a separate standalone Cellular IOT system. We analyze the architectural implication on the core network load in a tightly coupled CIOT-LTE architecture propose a offload mechanism from LTE to CIOT cells.

As the amount of mobile devices populating the Internet keeps growing at tremendous pace, context-aware services have gained a lot of traction thanks to the wide set of potential use cases they can be applied to. Environmental sensing applications, emergency services, and location-aware messaging are just a few examples of applications that are expected to increase in popularity in the next few years. The MobilityFirst future Internet architecture, a clean-slate Internet architecture design, provides the necessary abstractions for creating and managing context-aware services. Starting from these abstractions we design a context services framework, which is based on a set of three fundamental mechanisms: an easy way to specify context based on human understandable techniques, i.e. use of names, an architecture supported management mechanism that allows both to conveniently deploy the service and efficiently provide management capabilities, and a native delivery system that reduces the tax on the network components and on the overhead cost of deploying such applications. In this paper, we present an emergency alert system for vehicles assisting first responders that exploits users location awareness to support quick and reliable alert messages for interested vehicles. By deploying a demo of the system on a nationwide testbed, we aim to provide better understanding of the dynamics involved in our designed framework.

The Internet routing ecosystem is facing substantial scalability challenges on the data plane. Various “clean slate” architectures for representing forwarding tables (FIBs), such as IPv6, introduce additional constraints on efficient implementations from both lookup time and memory footprint perspectives due to significant classification width. In this work, we propose an abstraction layer able to represent IPv6 FIBs on existing IP and even MPLS infrastructure. Feasibility of the proposed representations is confirmed by an extensive simulation study on real IPv6 forwarding tables, including low-level experimental performance evaluation.

Internet of Things(IoT) is the next big boom in the networking field. The vision of IoT is to connect daily used objects (which have the ability of sensing and actuation) to the Internet. This may or may or may not involve human. IoT field is still maturing and has many open issues. We build up on the security issues. As the devices have low computational power and low memory the existing security mechanisms (which are a necessity) should also be optimized accordingly or a clean slate approach needs to be followed. This is a survey paper to focus on the security aspects of IoT. We further also discuss the open challenges in this field.

Control theory and SDN (Software Defined Networking) are key components for NFV (Network Function Virtualization) deployment. However little has been done to use a control-theoretic approach for SDN and NFV management. In this demo, we describe a use case for NFV management using control theory and SDN. We use the management architecture of RINA (a clean-slate Recursive InterNetwork Architecture) to manage Virtual Network Function (VNF) instances over the GENI testbed. We deploy Snort, an Intrusion Detection System (IDS) as the VNF. Our network topology has source and destination hosts, multiple IDSes, an Open vSwitch (OVS) and an OpenFlow controller. A distributed management application running on RINA measures the state of the VNF instances and communicates this information to a Proportional Integral (PI) controller, which then provides load balancing information to the OpenFlow controller. The latter controller in turn updates traffic flow forwarding rules on the OVS switch, thus balancing load across the VNF instances. This demo demonstrates the benefits of using such a control-theoretic load balancing approach and the RINA management architecture in virtualized environments for NFV management. It also illustrates that the GENI testbed can easily support a wide range of SDN and NFV related experiments.

Simple connectivity and data requirements together with high lifetime of battery are the main issues for the machine-to-machine (M2M) communications. 3GPP focuses on three main licensed standardizations based on Long Term Evolution (LTE), GSM and clean-slate technologies. The paper considers the last one and proposes a modified slotted-Aloha method to increase the capability of supporting a massive number of low-throughput devices. The proposed method increases the access rate of users belonging to each class considered in the clean-slate standard and consequently the total throughput offered by the system. To derive the mean access rate per class, we use the Markov chain approach and simulation results are provided for scenarios with different data rate and also in terms of cell average delay.