Jin Y, Wei D, Vural S, Gluhak A, Moessner K (2011) A distributed energy-efficient re-clustering solution for wireless sensor networks, GLOBECOM - IEEE Global Telecommunications Conference
Clustering algorithms are widely used in Wireless Sensor Networks (WSNs), which however incurs significant energy consumption at Cluster Headers(CHs). Therefore, a re-clustering operation is typically used to balance the workload, where different CHs are selected and clusters are reorganized. However, a considerable number of control messages is initiated during this process which inevitably consumes on-board node energy. Hence, the question of how often the network should perform the re-clustering operation needs to be addressed. In this paper, a distributed re-clustering solution is proposed, which provides an energy-efficient re-clustering rate to conserve node energy while also equalizing the node energy consumption across the network. The proposed algorithm calculates the approximate amount of energy required to reorganize the clusters and to deliver the sensory data. By properly predicting the levels of the energy consumptions values, the appropriate frequency of performing the re-clustering operation can be determined, which reduces control message overhead. To the best of our knowledge, this is the first work that analytically analyzes the overhead in re-clustering a WSN, groups re-clustering rounds to reduce this overhead, and simultaneously equalizes node lifetimes. Performance results show that the proposed algorithm outperforms two other popular clustering algorithms in node energy conservation and node lifetime equalization. © 2011 IEEE.
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.
The Internet-of-Things (IoT) paradigm envisions billions
of devices all connected to the Internet, generating low-rate
monitoring and measurement data to be delivered to application
servers or end-users. Recently, the possibility of applying innetwork
data caching techniques to IoT traffic flows has been
discussed in research forums. The main challenge as opposed to
the typically cached content at routers, e.g. multimedia files, is
that IoT data are transient and therefore require different caching
policies. In fact, the emerging location-based services can also
benefit from new caching techniques that are specifically designed
for small transient data. This paper studies in-network caching
of transient data at content routers, considering a key temporal
data property: data item lifetime. An analytical model that
captures the trade-off between multihop communication costs and
data item freshness is proposed. Simulation results demonstrate
that caching transient data is a promising information-centric
networking technique that can reduce the distance between
content requesters and the location in the network where the
content is fetched from. To the best of our knowledge, this is
a pioneering research work aiming to systematically analyse the
feasibility and benefit of using Internet routers to cache transient
data generated by IoT applications.
Al Kiyumi R, Vural S, Foh CH, Tafazolli R (2015) A Distributed Sleep Mechanism for Energy-Efficiency in Non-Beacon-Enabled IEEE 802.15.4 Networks, 2015 IEEE 20TH INTERNATIONAL WORKSHOP ON COMPUTER AIDED MODELLING AND DESIGN OF COMMUNICATION LINKS AND NETWORKS (CAMAD) pp. 237-241 IEEE
Vural S, Navaratnam, Wang N, Wang C, Dong L, Tafazolli R (2014) In-network Caching of Internet-of-Things,
Kim T-S, Broustis I, Vural S, Syrivelis D, Singh S, Krishnamurthy SV, La Porta TF (2012) Realizing the Benefits of Wireless Network Coding in Multirate Settings, IEEE ACM Transactions on Networking
Network coding has been proposed as a technique that can potentially increase the transport capacity of a wireless network via mixing data packets at intermediate routers. However, most previous studies either assume a fixed transmission rate or do not consider the impact of using diverse rates on the network coding gain. Since in many cases, network coding implicitly relies on overhearing, the choice of the transmission rate has a big impact on the achievable gains. The use of higher rates works in favor of increasing the native throughput. However, it may in many cases work against effective overhearing. In other words, there is a tension between the achievable network coding gain and the inherent rate gain possible on a link. In this paper, our goal is to drive the
network toward achieving the best tradeoff between these two contradictory effects.We design a distributed framework that: 1) facilitates the choice of the best rate on each link while considering the need for overhearing; and 2) dictates the choice of which decoding recipient will acknowledge the reception of an encoded packet. We demonstrate that both of these features contribute significantly toward gains in throughput.We extensively simulate our framework in a variety of topological settings. We also fully implement it on real hardware and demonstrate its applicability and performance gains via proof-of-concept experiments on our wireless testbed. We show that our framework yields throughput gains of up to 390% as compared to what is achieved in a rate-unaware network coding framework.
Vural S, Navaratnam P, Tafazolli R (2012) Transmission Range Assignment for Backbone Connectivity in Clustered Wireless Networks, IEEE Wireless Communications Letters
Data collection is a fundamental task of Wireless Sensor Networks (WSN) to support a variety of applications, such as remote monitoring, and emergency response, where collected information is relayed to an infrastructure network via packet gateways for processing and decision making. In large-scale monitoring scenarios, data packets need to be relayed over multi-hop paths to the gateways, and sensors are often randomly deployed, causing local node density differences. As a result, imbalance in data traffic load on the gateways is likely to occur. Furthermore, due to dynamic network conditions and differences in sensor data generation rates, congestion on some data paths is also often experienced. Numerous studies have focused on the problem of in-network traffic load balancing, while a few works have aimed at equalizing the loads on gateways. However, there is a potential trade-off between these two problems. In this paper, the dual objective of gateway and in-network load balancing is addressed and the RALB (Reactive and Adaptive Load Balancing) algorithm is presented. RALB is proposed as a generic solution for multihop networks and mesh topologies, especially in large-scale remote monitoring scenarios, to balance traffic loads.
Felemban E, Vural S, Murawski R, Ekici E, Lee K, Moon Y, Park S (2010) SAMAC: A Cross-Layer Communication Protocol for Sensor Networks with Sectored Antennas, Transactions on Mobile Computing 9 (8) pp. 1072-1088 IEEE
Vural S, Navaratnam P, Wang N, Tafazolli R (2014) Asynchronous Clustering of Multihop Wireless Sensor Networks, IEEE International Conference on Communications (ICC), 2014 pp. 472-477 IEEE
Node clustering has been widely studied in recent years for Wireless Sensor Networks (WSN) as a technique to form a hierarchical structure and prolong network lifetime by reducing the number of packet transmissions. Cluster Heads (CH) are elected in a distributed way among sensors, but are often highly overloaded, and therefore re-clustering operations should be performed to share the resource intensive CH-role. Existing protocols involve periodic network-wide re-clustering operations that are simultaneously performed, which requires global time synchronisation. To address this issue, some recent studies have proposed asynchronous node clustering for networks with direct links from CHs to the data sink. However, for large-scale WSNs, multihop packet delivery to the sink is required since longrange transmissions are costly for sensor nodes. In this paper, we present an asynchronous node clustering protocol designed for multihop WSNs, considering dynamic conditions such as residual node energy levels and unbalanced data traffic loads caused by packet forwarding. Simulation results demonstrate that it is possible to achieve similar levels of lifetime extension by re-clustering a multihop WSN via independently made decisions at CHs, without a need for time synchronisation required by existing synchronous protocols.
Pilloni V, Navaratnam P, Vural S, Atzori L, Tafazolli R (2013) Cooperative task assignment for distributed deployment of applications in WSNs, IEEE International Conference on Communications pp. 2229-2234
Nodes in Wireless Sensor Networks (WSNs) are becoming more and more complex systems with the capabilities to run distributed structured applications. Which single task should be implemented by each WSN node needs to be decided by the application deployment strategy by taking into account both network lifetime and execution time requirements. In this paper, we propose an adaptive decentralised algorithm based on noncooperative game theory, where neighbouring nodes negotiate among each other to maximize their utility function. We then prove that an increment of the nodes utility corresponds to the same increment of the utility for the whole network. Simulation results show significant performance improvement with respect to existing algorithms. © 2013 IEEE.
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.
Pilloni V, Navaratnam P, Vural S, Atzori L, Tafazolli R (2013) TAN: A distributed algorithm for dynamic task assignment in WSNs, IEEE Sensors Journal 14 (4) pp. 1266-1279
We consider the scenario of wireless sensor networks where a given application has to be deployed and each application task has to be assigned to each node in the best possible way. Approaches where decisions on task execution are taken by a single central node can avoid the exchange of data packets between task execution nodes but cannot adapt to dynamic network conditions, and suffer from computational complexity. To address this issue, in this paper, we propose an adaptive and decentralized task allocation negotiation algorithm (TAN) for cluster network topologies. It is based on noncooperative game theory, where neighboring nodes engage in negotiations to maximize their own utility functions to agree on which of them should execute single application tasks. Performance is evaluated in a city scenario, where the urban streets are equipped with different sensors and the application target is the detection of the fastest way to reach a destination, and in random WSN scenarios. Comparisons are made with three other algorithms: 1) baseline setting with no task assignment to multiple nodes; 2) centralized task assignment lifetime optimization; and 3) a dynamic distributed algorithm, DLMA. The result is that TAN outperforms these algorithms in terms of application completion time and average energy consumption. © 2001-2012 IEEE.
In this letter, we analyse the trade-off between collision probability and code-ambiguity, when devices transmit a sequence of preambles as a codeword, instead of a single preamble, to reduce collision probability during random access to a mobile network. We point out that the network may not have sufficient resources to allocate to every possible codeword, and if it does, then this results in low utilisation of allocated uplink resources. We derive the optimal preamble set size that maximises the probability of success in a single attempt, for a given number of devices and uplink resources.
The random access (RA) mechanism of Long Term
Evolution (LTE) networks is prone to congestion when a large
number of devices attempt RA simultaneously, due to the
limited set of preambles. If each RA attempt is made by means
of transmission of multiple consecutive preambles (codewords)
picked from a subset of preambles, as proposed in , collision
probability can be significantly reduced. Selection of an optimal
preamble set size  can maximise RA success probability in the
presence of a trade-off between codeword ambiguity and code
collision probability, depending on load conditions. In light of this
finding, this paper provides an adaptive algorithm, called Multipreamble
RA, to dynamically determine the preamble set size
in different load conditions, using only the minimum necessary
uplink resources. This provides high RA success probability, and
makes it possible to isolate different network service classes by
separating the whole preamble set into subsets each associated
to a different service class; a technique that cannot be applied
effectively in LTE due to increased collision probability. This
motivates the idea that preamble allocation could be implemented
as a virtual network function, called vPreamble, as part of
a random access network (RAN) slice. The parameters of a
vPreamble instance can be configured and modified according
to the load conditions of the service class it is associated to.
Energy consumption of sensor nodes is a key factor affecting the lifetime of wireless sensor networks (WSNs). Prolonging network lifetime not only requires energy efficient operation, but also even dissipation of energy among sensor nodes. On the other hand, spatial and temporal variations in sensor activities create energy imbalance across the network. Therefore, routing algorithms should make an appropriate trade-off between energy efficiency and energy consumption balancing to extend the network lifetime. In this paper, we propose a Distributed Energy-aware Fuzzy Logic based routing algorithm (DEFL) that simultaneously addresses energy efficiency and energy balancing. Our design captures network status through appropriate energy metrics and maps them into corresponding cost values for the shortest path calculation. We seek fuzzy logic approach for the mapping to incorporate human logic. We compare the network lifetime performance of DEFL with other popular solutions including MTE, MDR and FA. Simulation results demonstrate that the network lifetime achieved by DEFL exceeds the best of all tested solutions under various traffic load conditions. We further numerically compute the upper bound performance and show that DEFL performs near the upper bound.
Software-Defined Networking (SDN) is a promising
paradigm of computer networks, offering a programmable and
centralised network architecture. However, although such a
technology supports the ability to dynamically handle network
traffic based on real-time and flexible traffic control, SDN-based
networks can be vulnerable to dynamic change of flow control
rules, which causes transmission disruption and packet loss in
SDN hardware switches. This problem can be critical because the
interruption and packet loss in SDN switches can bring additional
performance degradation for SDN-controlled traffic flows in the
data plane. In this paper, we propose a novel robust flow control
mechanism referred to as Priority-based Flow Control (PFC)
for dynamic but disruption-free flow management when it is
necessary to change flow control rules on the fly. PFC minimizes
the complexity of flow modification process in SDN switches
by temporarily adapting the priority of flow rules in order to
substantially reduce the time spent on control-plane processing
during run-time. Measurement results show that PFC is able
to successfully prevent transmission disruption and packet loss
events caused by traffic path changes, thus offering dynamic and
lossless traffic control for SDN switches.