Socio-economic aware data forwarding in mobile sensing networks and systems

The vision for smart sustainable cities is one whereby urban sensing is core to optimising city operation which in turn improves citizen contentment. Wireless Sensor Networks are envisioned to become pervasive form of data collection and analysis for smart cities but deployment of millions of inter-connected sensors in a city can be cost-prohibitive. Given the ubiquity and ever-increasing capabilities of sensor-rich mobile devices, Wireless Sensor Networks with Mobile Phones (WSN-MP) provide a highly flexible and ready-made wireless infrastructure for future smart cities. In a WSN-MP, mobile phones not only generate the sensing data but also relay the data using cellular communication or short range opportunistic communication. The largest challenge here is the efficient transmission of potentially huge volumes of sensor data over sometimes meagre or faulty communications networks in a cost-effective way. This thesis investigates distributed data forwarding schemes in three types of WSN-MP: WSN with mobile sinks (WSN-MS), WSN with mobile relays (WSN-HR) and Mobile Phone Sensing Systems (MPSS). For these dynamic WSN-MP, realistic models are established and distributed algorithms are developed for efficient network performance including data routing and forwarding, sensing rate control and and pricing. This thesis also considered realistic urban sensing issues such as economic incentivisation and demonstrates how social network and mobility awareness improves data transmission. Through simulations and real testbed experiments, it is shown that proposed algorithms perform better than state-of-the-art schemes.Open Acces

From MANET to people-centric networking: Milestones and open research challenges

In this paper, we discuss the state of the art of (mobile) multi-hop ad hoc networking with the aim to present the current status of the research activities and identify the consolidated research areas, with limited research opportunities, and the hot and emerging research areas for which further research is required. We start by briefly discussing the MANET paradigm, and why the research on MANET protocols is now a cold research topic. Then we analyze the active research areas. Specifically, after discussing the wireless-network technologies, we analyze four successful ad hoc networking paradigms, mesh networks, opportunistic networks, vehicular networks, and sensor networks that emerged from the MANET world. We also present an emerging research direction in the multi-hop ad hoc networking field: people centric networking, triggered by the increasing penetration of the smartphones in everyday life, which is generating a people-centric revolution in computing and communications

A Survey on Mobile Crowdsensing Systems: Challenges, Solutions, and Opportunities

Mobile crowdsensing (MCS) has gained significant attention in recent years and has become an appealing paradigm for urban sensing. For data collection, MCS systems rely on contribution from mobile devices of a large number of participants or a crowd. Smartphones, tablets, and wearable devices are deployed widely and already equipped with a rich set of sensors, making them an excellent source of information. Mobility and intelligence of humans guarantee higher coverage and better context awareness if compared to traditional sensor networks. At the same time, individuals may be reluctant to share data for privacy concerns. For this reason, MCS frameworks are specifically designed to include incentive mechanisms and address privacy concerns. Despite the growing interest in the research community, MCS solutions need a deeper investigation and categorization on many aspects that span from sensing and communication to system management and data storage. In this paper, we take the research on MCS a step further by presenting a survey on existing works in the domain and propose a detailed taxonomy to shed light on the current landscape and classify applications, methodologies, and architectures. Our objective is not only to analyze and consolidate past research but also to outline potential future research directions and synergies with other research areas

Optimized query routing trees for wireless sensor networks

In order to process continuous queries over Wireless Sensor Networks (WSNs), sensors are typically organized in a Query Routing Tree (denoted as T) that provides each sensor with a path over which query results can be transmitted to the querying node. We found that current methods deployed in predominant data acquisition systems construct T in a sub-optimal manner which leads to significant waste of energy. In particular, since T is constructed in an ad hoc manner there is no guarantee that a given query workload will be distributed equally among all sensors. That leads to data collisions which represent a major source of energy waste. Additionally, current methods only provide a topological-based method, rather than a query-based method, to define the interval during which a sensing device should enable its transceiver in order to collect the query results from its children. We found that this imposes an order of magnitude increase in energy consumption. In this paper we present MicroPulse+, a novel framework for minimizing the consumption of energy during data acquisition in WSNs. MicroPulse+ continuously optimizes the operation of T by eliminating data transmission and data reception inefficiencies using a collection of in-network algorithms. In particular, MicroPulse+ introduces: (i) the Workload-Aware Routing Tree (WART) algorithm, which is established on profiling recent data acquisition activity and on identifying the bottlenecks using an in-network execution of the critical path method; and (ii) the Energy-driven Tree Construction (ETC) algorithm, which balances the workload among nodes and minimizes data collisions. We show through micro-benchmarks on the CC2420 radio chip and trace-driven experimentation with real datasets from Intel Research and UC-Berkeley that MicroPulse+ provides significant energy reductions under a variety of conditions thus prolonging the longevity of a wireless sensor network

An Energy Efficient, Load Balancing, and Reliable Routing Protocol for Wireless Sensor Networks

AN ENERGY EFFICIENT, LOAD BALANCING, AND RELIABLE ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORKS by Kamil Samara The University of Wisconsin-Milwaukee, 2016 Under the Supervision of Professor Hossein Hosseini The Internet of Things (IoT) is shaping the future of Computer Networks and Computing in general, and it is gaining ground very rapidly. The whole idea has originated from the pervasive presence of a variety of things or objects equipped with the internet connectivity. These devices are becoming cheap and ubiquitous, at the same time more powerful and smaller with a variety of onboard sensors. All these factors with the availability of unique addressing, provided by the IPv6, has made these devices capable of collaborating with each other to accomplish common tasks. Mobile AdHoc Networks (MANETS) and Wireless Sensor Networks (WSN) in particular play a major role in the backbone of IoT. Routing in Wireless Sensor Networks (WSN) has been a challenging task for researchers in the last several years because the conventional routing algorithms, such as the ones used in IP-based networks, are not well suited for WSNs because these conventional routing algorithms heavily rely on large routing tables that need to be updated periodically. The size of a WSN could range from hundreds to tens of thousands of nodes, which will make routing tables’ size very large. Managing large routing tables is not feasible in WSNs due to the limitations of resources. The directed diffusion algorithm is a well-known routing algorithm for Wireless Sensor Networks (WSNs). The directed diffusion algorithm saves energy by sending data packets hop by hop and by enforcing paths to avoid flooding. The directed diffusion algorithm does not attempt to find the best or healthier paths (healthier paths are paths that use less total energy than others and avoid critical nodes). Hence the directed diffusion algorithm could be improved by enforcing the use of healthier paths, which will result in less power consumption. We propose an efficient routing protocol for WSNs that gives preference to the healthier paths based on the criteria of the total energy available on the path, the path length, and the avoidance of critical nodes. This preference is achieved by collecting information about the available paths and then using non-incremental machine learning to enforce path(s) that meet our criteria. In addition to preferring healthier paths, our protocol provides Quality of Service (QoS) features through the implementation of differentiated services, where packets are classified as critical, urgent, and normal, as defined later in this work. Based on this classification, different packets are assigned different priority and resources. This process results in higher reliability for the delivery of data, and shorter delivery delay for the urgent and critical packets. This research includes the implementation of our protocol using a Castalia Simulator. Our simulation compares the performance of our protocol with that of the directed diffusion algorithm. The comparison was made on the following aspects: • Energy consumption • Reliable delivery • Load balancing • Network lifetime • Quality of service Simulation results did not point out a significant difference in performance between the proposed protocol and the directed diffusion algorithm in smaller networks. However, when the network’s size started to increase the results showed better performance by the proposed protocol