Athanasios Kinalis

Sink mobility protocols for data collection in wireless sensor networks

In wireless sensor networks data propagation is usually performed by sensors transmitting data towards a static control center (sink). Inspired by important applications (mostly related to ambient intelligence) and as a first step towards introducing mobility, we propose the idea of having a sink moving in the network area and collecting data from sensors. We propose four characteristic mobility patterns for the sink along with different data collection strategies. Through a detailed simulation study, we evaluate several important performance properties of each protocol. Our findings demonstrate that by taking advantage of the sinks mobility, we can significantly reduce the energy spent in relaying traffic and thus greatly extend the lifetime of the network.

Efficient data propagation strategies in wireless sensor networks using a single mobile sink

Data collection is usually performed in wireless sensor networks by the sensors relaying data towards a static control center (sink). Motivated by important applications (mostly related to ambient intelligence and remote monitoring) and as a first step towards introducing mobility, we propose the basic idea of having a sink moving in the network area and collecting data from sensors. We propose four characteristic mobility patterns for the sink that we combine with different data collection strategies. Through a detailed simulation study, we evaluate several important performance properties of each approach. Our findings demonstrate that by taking advantage of the sinks mobility and shifting work from sensors to the powerful sink, we can significantly reduce the energy spent in relaying traffic and thus greatly extend the lifetime of the network.

Full Length Article: Biased sink mobility with adaptive stop times for low latency data collection in sensor networks

Collecting sensory data using a mobile data sink has been shown to drastically reduce energy consumption at the cost of increasing delivery delay. Towards improved energy-latency trade-offs, we propose a biased, adaptive sink mobility scheme, that adjusts to local network conditions, such as the surrounding density, remaining energy and the number of past visits in each network region. The sink moves probabilistically, favoring less visited areas in order to cover the network area faster, while adaptively stopping more time in network regions that tend to produce more data. We implement and evaluate our mobility scheme via simulation in diverse network settings. Compared to known blind random, non-adaptive schemes, our method achieves significantly reduced latency, especially in networks with non-uniform sensor distribution, without compromising the energy efficiency and delivery success.

Energy efficient protocols for sensing multiple events in Smart Dust networks

Wireless sensor networks are comprised of a vast number of ultra-small, autonomous computing and communication devices, with restricted energy, that cooperate to accomplish a large sensing task. In this work: a) we propose extended versions of two data propagation protocols for such networks: the sleep-awake probabilistic forwarding protocol (SW-PFR) and the hierarchical threshold sensitive energy efficient network protocol (H-TEEN). These non-trivial extensions improve the performance of the original protocols, by introducing sleep-awake periods in the PFR protocol to save energy, and introducing a hierarchy of clustering in the TEEN protocol to better cope with large networks; b) we implemented the two protocols and performed an extensive simulation comparison of various important measures of their performance with a focus on energy consumption; c) we investigate in detail the relative advantages and disadvantages of each protocol; and d) we discuss a possible hybrid combination of the two protocols towards optimizing certain goals.

Priority based adaptive coordination of wireless sensors and actors

Wireless sensor and actor networks are comprised of a large number of small, fully autonomous computing, communication, sensing and actuation devices, with very restricted energy and computing capabilities. Such devices co-operate to accomplish a large sensing and acting task. Sensors gather information for an event in the physical world and notify the actors that perform appropriate actions by making a decision on receipt of the sensed information. Such networks can be very useful in practice i.e. in the local detection of remote crucial events and the propagation of relevant data to decision centers that perform appropriate actions upon the environment, thus realizing sensing and acting from a distanceIn this work we present a communication protocol that enables scalable, energy efficient and fault tolerant coordination while allowing to prioritize sensing tasks in situated wireless sensor and actor networks. The sensors react locally on environment and context changes and interact with each other in order to adjust the performance of the network in terms of energy, latency and success rate on a per-task basis. To deal with the increased complexity of such large-scale systems, our protocol pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the actors. We implement and evaluate the protocol using large scale simulation, showing its suitability in networks where sensor to actor and actor to actor coordination are important for accomplishing tasks of different priorities

Fast and energy efficient sensor data collection by multiple mobile sinks

We investigate the impact of multiple, mobile sinks on efficient data collection in wireless sensor networks. To improve performance, our protocol design focuses on minimizing overlaps of sink trajectories and balancing the service load among the sinks. To cope with high network dynamics, placement irregularities and limited network knowledge we propose three different protocols: a) a centralized one, that explicitly equalizes spatial coverage; this protocol assumes strong modeling assumptions, and also serves as a kind of performance lower bound in uniform networks of low dynamics b) a distributed protocol based on mutual avoidance of sinks c) a clustering protocol that distributively groups service areas towards balancing the load per sink. Our simulation findings demonstrate significant gains in latency, while keeping the success rate and the energy dissipation at very satisfactory levels even under high network dynamics and deployment heterogeneity.

Scalable Data Collection Protocols for Wireless Sensor Networks with Multiple Mobile Sinks

Data propagation in wireless sensor networks is usually performed as a multihop process. To deliver a single message, the resources of many sensor nodes are used and a lot of energy is spent. Recently, a novel approach is catching momentum because of important applications; that of having a mobile sink move inside the network area and collects the data with low energy cost. Here we extend this line of research by proposing and evaluating three new protocols. Our protocols are novel in a) investigating the impact of having many mobile sinks; b) in weak models with restricted mobility, proposing and evaluating a mix of static and mobile sinks; and c) proposing a distributed protocol that tends to equally spread the sinks in the network to further improve performance. Our protocols are simple, based on randomization and assume locally obtainable information. We perform an extensive evaluation via simulation; our findings demonstrate that our solutions scale very well with respect to the number of sinks and significantly reduce energy consumption and delivery delay

Wireless sensor networks protocols for efficient collision avoidance in multi-path data propagation

Data propagation in wireless sensor networks can be performed either by hop-by-hop single transmissions or by multi-path broadcast of data. Although several energy-aware MAC layer protocols exist that operate very well in the case of single point-to-point transmissions, none is especially designed and suitable for multiple broadcast transmissions.In this paper we propose a family of new protocols suitable of multi-path broadcast of data, and show, through a detailed and extended simulation evaluation, that our parameter-based protocols significantly reduce the number of collisions and thus increase the rate of successful message delivery (to above 90%) by trading off the average propagation delay. At the same time, our protocols are shown to be very energy efficient, in terms of the average energy dissipation per delivered message.

Power Conservation Schemes for Energy Efficient Data Propagation in Heterogeneous Wireless Sensor Networks

We propose, implement and evaluate new energy conservation schemes for efficient data propagation in wireless sensor networks. Our protocols are adaptive, i.e. locally monitor the network conditions and accordingly adjust towards optimal operation choices. This dynamic feature is particularly beneficial in heterogeneous settings and in cases of redeployment of sensor devices in the network area. We implement our protocols and evaluate their performance through a detailed simulation study using our extended version of ns-2. In particular we combine our schemes with known communication paradigms. The simulation findings demonstrate significant gains and good trade-offs in terms of delivery success, delay and energy dissipation.

Adaptive redundancy for data propagation exploiting dynamic sensory mobility

Motivated by emerging applications, we consider sensor networks where the sensors themselves (not just the sinks) are mobile. We focus on mobility scenarios characterized by heterogeneous, highly changing mobility roles in the network. To capture these high dynamics we propose a novel network parameter, the mobility level, which, although simple and local, quite accurately takes into account both the spatial and speed characteristics of motion. We then propose adaptive data dissemination protocols that use the mobility level estimation to improve performance. By basically exploiting high mobility (redundant message ferrying) as a cost-effective replacement of flooding, e.g., the sensors tend to dynamically propagate less data in the presence of high mobility, while nodes of high mobility are favored for moving data around. These dissemination schemes are enhanced by a distance-sensitive probabilistic message flooding inhibition mechanism that further reduces communication cost, especially for fast nodes of high mobility level, and as distance to data destination decreases. Our simulation findings demonstrate significant performance gains of our protocols compared to non-adaptive protocols, i.e., adaptation increases the success rate and reduces latency (even by 15%) while at the same time significantly reducing energy dissipation (in most cases by even 40%). Also, our adaptive schemes achieve significantly higher message delivery ratio and satisfactory energy-latency trade-offs when compared to flooding when sensor nodes have limited message queues.