Serdar Vural

Probabilistic QoS guarantee in reliability and timeliness domains in wireless sensor networks

In this paper, we present a novel packet delivery mechanism called multi-path and multi-speed routing protocol (MMSPEED) for probabilistic QoS guarantee in wireless sensor networks. The QoS provisioning is performed in two quality domains, namely, timeliness and reliability. Multiple QoS levels are provided in the timeliness domain by guaranteeing multiple packet delivery speed options. In the reliability domain, various reliability requirements are supported by probabilistic multipath forwarding. All these for QoS provisioning are realized in a localized way without global network information by employing localized geographic packet forwarding augmented with dynamic compensation, which compensates the local decision inaccuracy as a packet travels towards its destination. This way, MMSPEED can guarantee end-to-end requirements in a localized way, which is desirable for scalability and adaptability to large scale dynamic sensor networks. Simulation results show that MMSPEED provides QoS differentiation in both reliability and timeliness domains and, as a result, significantly improves the effective capacity of a sensor network in terms of number of flows that meet both reliability and timeliness requirements.

An Energy-Efficient Clustering Solution for Wireless Sensor Networks

Hot spots in a wireless sensor network emerge as locations under heavy traffic load. Nodes in such areas quickly deplete energy resources, leading to disruption in network services. This problem is common for data collection scenarios in which Cluster Heads (CH) have a heavy burden of gathering and relaying information. The relay load on CHs especially intensifies as the distance to the sink decreases. To balance the traffic load and the energy consumption in the network, the CH role should be rotated among all nodes and the cluster sizes should be carefully determined at different parts of the network. This paper proposes a distributed clustering algorithm, Energy-efficient Clustering (EC), that determines suitable cluster sizes depending on the hop distance to the data sink, while achieving approximate equalization of node lifetimes and reduced energy consumption levels. We additionally propose a simple energy-efficient multihop data collection protocol to evaluate the effectiveness of EC and calculate the end-to-end energy consumption of this protocol; yet EC is suitable for any data collection protocol that focuses on energy conservation. Performance results demonstrate that EC extends network lifetime and achieves energy equalization more effectively than two well-known clustering algorithms, HEED and UCR.

On Multihop Distances in Wireless Sensor Networks with Random Node Locations

Location and intersensor distance estimations are important functions for the operation of wireless sensor networks, especially when protocols can benefit from the distance information prior to network deployment. The maximum multihop distance that can be covered in a given number of hops in a sensor network is one such parameter related with coverage area, delay, and minimal multihop transmission energy consumption estimations. In randomly deployed sensor networks, intersensor distances are random variables. Hence, their evaluations require probabilistic methods, and distance models should involve investigation of distance distribution functions. Current literature on analytical modeling of the maximum distance distribution is limited to 1D networks using the Gaussian pdf. However, determination of the maximum multihop distance distribution in 2D networks is a quite complex problem. Furthermore, distance distributions in 2D networks are not accurately modeled by the Gaussian pdf. Hence, we propose a greedy method of distance maximization and evaluate the distribution of the obtained multihop distance through analytical approximations and simulations.

Secure probabilistic location verification in randomly deployed wireless sensor networks

Security plays an important role in the ability to deploy and retrieve trustworthy data from a wireless sensor network. Location verification is an effective defense against attacks which take advantage of a lack, or compromise, of location information. In this work, a secure probabilistic location verification method for randomly deployed dense sensor networks is proposed. The proposed Probabilistic Location Verification (PLV) algorithm leverages the probabilistic dependence of the number of hops a broadcast packet traverses to reach a destination and the Euclidean distance between the source and the destination. A small number of verifier nodes are used to determine the plausibility of the claimed location, which is represented by a real number between zero and one. Using the calculated plausibility metric, it is possible to create arbitrary number of trust levels in the location claimed. Simulation studies verify that the proposed solution provides high performance in face of various types of attacks.

Analysis of hop-distance relationship in spatially random sensor networks

In spatially random sensor networks, estimating the Euclidean distance covered by a packet in a given number of hops carries a high importance for various other methods such as localization and distance estimations. The inaccuracies in such estimations motivate this study on the distribution of the Euclidean distance covered by a packet in spatially random sensor networks in a given number of hops. Although a closed-form expression of distance distribution cannot be obtained, highly accurate approximations are derived for this distribution in one dimensional spatially random sensor networks. Using statistical measures and numerical examples, it is also shown that the presented distribution approximation yields very high accuracy even for small number of hops. A discussion on how these principles can be extended to the analysis of the same problem in two dimensional networks is also provided.

Survey of Experimental Evaluation Studies for Wireless Mesh Network Deployments in Urban Areas Towards Ubiquitous Internet

Establishing wireless networks in urban areas that can provide ubiquitous Internet access to end-users is a central part of the efforts towards defining the Internet of the future. In recent years, Wireless Mesh Network (WMN) backbone infrastructures are proposed as a cost effective technology to provide city-wide Internet access. Studies that evaluate the performance of city-wide mesh network deployments via experiments provide essential information on various challenges of building them. In this survey, we particularly focus on such studies and provide brief conclusions on the problems, benefits, and future research directions of city-wide WMNs.

SAMAC: A Cross-Layer Communication Protocol for Sensor Networks with Sectored Antennas

Wireless sensor networks have been used to gather data and information in many diverse application settings. The capacity of such networks remains a fundamental obstacle toward the adaptation of sensor network systems for advanced applications that require higher data rates and throughput. In this paper, we explore potential benefits of integrating directional antennas into wireless sensor networks. While the usage of directional antennas has been investigated in the past for ad hoc networks, their usage in sensor networks bring both opportunities as well as challenges. In this paper, Sectored-Antenna Medium Access Control (SAMAC), an integrated cross-layer protocol that provides the communication mechanisms for sensor network to fully utilize sectored antennas, is introduced. Simulation studies show that SAMAC delivers high energy efficiency and predictable delay performance with graceful degradation in performance with increased load.

Probability distribution of multi-hop-distance in one-dimensional sensor networks

In spatially random sensor networks, estimating the Euclidean distance covered by a packet in a given number of hops carries a high importance for various functions such as localization and distance estimations. The inaccuracies in such estimations motivate this study on the distribution of the Euclidean distance covered by a packet in spatially random sensor networks in a given number of hops. Although a closed-form expression of distance distribution cannot be obtained, highly accurate approximations are derived for this distribution in one-dimensional spatially random sensor networks. Using statistical measures and numerical examples, it is also shown that the presented distribution approximation yields very high accuracy even for small number of hops. Furthermore, the distribution of hop distance that covers a given Euclidean distance is also approximated.

Enabling Massive IoT in 5G and Beyond Systems: PHY Radio Frame Design Considerations

The parameters of physical layer radio frame for 5th generation (5G) mobile cellular systems are expected to be flexibly configured to cope with diverse requirements of different scenarios and services. This paper presents a frame structure and design, which is specifically targeting Internet of Things (IoT) provision in 5G wireless communication systems. We design a suitable radio numerology to support the typical characteristics, that is, massive connection density and small and bursty packet transmissions with the constraint of low-cost and low complexity operation of IoT devices. We also elaborate on the design of parameters for random access channel enabling massive connection requests by IoT devices to support the required connection density. The proposed design is validated by link level simulation results to show that the proposed numerology can cope with transceiver imperfections and channel impairments. Furthermore, the results are also presented to show the impact of different values of guard band on system performance using different subcarrier spacing sizes for data and random access channels, which show the effectiveness of the selected waveform and guard bandwidth. Finally, we present system-level simulation results that validate the proposed design under realistic cell deployments and inter-cell interference conditions.

In-network caching of Internet-of-Things data

The recent forecast of billions of devices, all connected to the Internet and generating low-rate monitoring, measurement, or automation data that many end-users/applications frequently request, signifies the need for applying in-network caching techniques to Internet-of-Things (IoT) traffic. Although time delay is not critically important for small-sized IoT content, the expected total traffic load on the Internet from a large number of devices is significant. However, the main challenge as opposed to the typically cached content at content routers, e.g. multimedia files, is that IoT data are transient and therefore require different caching policies. This paper studies in-network caching of IoT data at content routers in the Internet. An IoT data item is uniquely defined not only by its time and location tags, but also a time-range value set by end-users/applications. We provide a model for the trade-off between multihop communication costs and the freshness of a transient data item. Results show that the model can successfully capture the effect of data transiency and can accurately represent the expected gains of a caching system: considerable savings in terms of reduction of network load, especially for highly requested data items.