Towards Opportunistic Data Dissemination in Mobile Phone Sensor Networks

Recently, there has been a growing interest within the research community in developing opportunistic routing protocols. Many schemes have been proposed; however, they differ greatly in assumptions and in type of network for which they are evaluated. As a result, researchers have an ambiguous understanding of how these schemes compare against each other in their specific applications. To investigate the performance of existing opportunistic routing algorithms in realistic scenarios, we propose a heterogeneous architecture including fixed infrastructure, mobile infrastructure, and mobile nodes. The proposed architecture focuses on how to utilize the available, low cost short-range radios of mobile phones for data gathering and dissemination. We also propose a new realistic mobility model and metrics. Existing opportunistic routing protocols are simulated and evaluated with the proposed heterogeneous architecture, mobility models, and transmission interfaces. Results show that some protocols suffer long time-to-live (TTL), while others suffer short TTL. We show that heterogeneous sensor network architectures need heterogeneous routing algorithms, such as a combination of Epidemic and Spray and Wait

Minimum Expected Delay-Based Routing Protocol (MEDR) for Delay Tolerant Mobile Sensor Networks

It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches

An Energy-Efficient MAC Protocol Using Dynamic Queue Management for Delay-Tolerant Mobile Sensor Networks

Conventional MAC protocols for wireless sensor network perform poorly when faced with a delay-tolerant mobile network environment. Characterized by a highly dynamic and sparse topology, poor network connectivity as well as data delay-tolerance, delay-tolerant mobile sensor networks exacerbate the severe power constraints and memory limitations of nodes. This paper proposes an energy-efficient MAC protocol using dynamic queue management (EQ-MAC) for power saving and data queue management. Via data transfers initiated by the target sink and the use of a dynamic queue management strategy based on priority, EQ-MAC effectively avoids untargeted transfers, increases the chance of successful data transmission, and makes useful data reach the target terminal in a timely manner. Experimental results show that EQ-MAC has high energy efficiency in comparison with a conventional MAC protocol. It also achieves a 46% decrease in packet drop probability, 79% increase in system throughput, and 25% decrease in mean packet delay

Social-context based routing and security in delay tolerant networks

Delay Tolerant Networks (DTNs) were originally intended for interplanetary communications and have been applied to a series of difficult environments: wireless sensor networks, unmanned aerial vehicles, and short-range personal communications. There is a class of such environments in which nodes follow semi-predictable social patterns, such as wildlife tracking or personal devices. This work introduces a series of algorithms designed to identify the social patterns present in these environments and apply this data to difficult problems, such as efficient message routing and content distribution. Security is also difficult in a mobile environment. This is especially the case in the event that a large portion of the network is unreliable, or simply unknown. As the network size increases nodes have difficulty in securely distributing keys, especially using low powered nodes with limited keyspace. A series of multi-party security algorithms were designed to securely transmit a message in the event that the sender does not have access to the destinations public key. Messages are routed through a series of nodes, each of which partially decrypts the message. By encrypting for several proxies, the message can only be intercepted if all those nodes have been compromised. Even a highly compromised network has increased security using this algorithm, with a trade-off of reduced delivery ratio and increased delivery time -- Abstract, page iv

An Effective Mobile Sensor Control Method for Sparse Sensor Networks

In this paper, we propose an effective mobile sensor control method, named DATFM (Data Acquisition and Transmission with Fixed and Mobile node) for sparse sensor networks. DATFM uses two types of sensor nodes, fixed node and mobile node. The data acquired by nodes are accumulated on a fixed node before being transferred to the sink node. In addition, DATFM transfers the accumulated data efficiently by constructing a communication route of multiple mobile nodes between fixed nodes. We also conduct simulation experiments to evaluate the performance of DATFM

Maximizing data survival in Unattended Wireless Sensor Networks against a focused mobile adversary

Some sensor network settings involve disconnected or unattended operation with periodic visits by a mobile sink. An unattended sensor network operating in a hostile environment can collect data that represents a high-value target for the adversary. Since an unattended sensor can not immediately off-load sensed data to a safe external entity (such as a sink), the adversary can easily mount a focused attack aiming to erase or modify target data. To maximize chances of data survival, sensors must collaboratively attempt to mislead the adversary and hide the location, the origin and the contents of collected data. In this paper, we focus on applications of well-known security techniques to maximize chances of data survival in unattended sensor networks, where sensed data can not be off-loaded to a sink in real time. Our investigation yields some interesting insights and surprising results. The highlights of our work are: (1) thorough exploration of the data survival challenge, (2) exploration of the design space for possible solutions, (3) construction of several practical and effective techniques, and (4) their evaluation