Regina Borges de Araujo

A fast and reliable protocol for wireless sensor networks in critical conditions monitoring applications

Sensor networks are increasingly being deployed for fine-grain monitoring of physical environments subjected to critical conditions such as fire, leaking of toxic gases and explosions. A great challenge to these networks is to provide a fast, reliable and fault tolerant channel for events diffusion, which meets the requirements of query-based, event-driven and periodic sensor networks application scenarios, even in the presence of emergency conditions that can lead to node failures and path disruption to the sink that receives those events. This paper presents a fault tolerant and low latency algorithm, which we refer to as PEQ (Periodic, Event-Driven and Query-Based Protocol), that meets sensor networks requirements for critical conditions surveillance applications. The algorithm uses the publish/subscribe paradigm to disseminate requests across the network and an ack-based scheme to provide fault tolerance. The algorithm was implemented using NS-2 simulator and compared to the Directed Diffusion paradigm. Important metrics were evaluated showing that the proposed algorithm can be a proper solution to meet constraints and requirements of events delivery in critical conditions monitoring applications.

Fault-tolerant wireless sensor network routing protocols for the supervision of context-aware physical environments

Applications that require fine-grain monitoring of physical environments subjected to critical conditions, such as fire, leaking of toxic gases and explosions, pose a great challenge to sensor network protocols. These networks have to provide a fast, reliable, fault-tolerant and energy-aware channel for events diffusion, which meets the requirements of query-based, event-driven and periodic sensor networks application scenarios. These requirements have to be met even in the presence of emergency conditions that can lead to node failures and path disruption to the sink. This paper proposes two routing protocols: periodic, event-driven and query-based protocol (PEQ) and its variation CPEQ, two fault-tolerant and low-latency algorithms that meet sensor network requirements for critical conditions supervision in context-aware physical environments. While PEQ can provide low latency for event notification, fast broken path reconfiguration, and high reliability in the delivery of event packets for low-network data traffic, CPEQ is a cluster-based routing protocol that groups sensor nodes to efficiently relay the sensed data to the sink by uniformly distributing energy dissipation among the nodes and reducing latency for high-network data traffic (typical in emergency situations). PEQ and its variant CPEQ use the publish/subscribe paradigm to disseminate requests across the network. We discuss both PEQ and CPEQ protocols, their implementation, and report on the performance results of several scenarios using NS-2 simulator. The results obtained are compared with the well-known directed diffusion (DD) protocol, and show that our proposed algorithms exhibit a clear indication to meet the constraints and requirements of critical condition supervision in context-aware physical environments. Our results indicate that PEQ outperforms DD in the average delay since it uses the shortest path for the delivery of packets and speed up new subscriptions by using the reverse path used for event notification packets. CPEQ also outperforms DD in both the average delay and in the packet delivery ratio when the network scales up.

An optimal coverage-preserving scheme for wireless sensor networks based on local information exchange

Coverage-preserving and energy-saving solutions have been reported in the literature and are generally based upon both quality coverage and off-duty scheme. Off-duty scheme based solutions present at least three challenging problems: (1) keeping coverage and connectivity of the network while optimizing the number of active sensor nodes; (2) resolving conflicts when determining which nodes should be turned off in order to save energy; and (3) finding optimal wake-up strategies that avoid waking up more nodes than necessary. This paper presents a novel distributed solution, the optimal coverage-preserving scheme (OCoPS), that extends the well-known Central Angle Method in order to identify fully sponsored nodes. OCoPS comprises an extended Central Angle Method, new decision algorithms devised to resolve the off-duty conflict problem under different network densities, and an energy-aware wake-up scheme that solves coverage hole problems in off-duty schemes. Compared to the widely used node scheduling scheme, our solution is based on local information exchange without the uncertainty of self-schedule algorithms. OCoPS is implemented as an extension of LEACH. A set of simulation experiments is carried out to evaluate its performance compared to other well-known schemes which are based on the Central Angle Method and self-scheduling. Our results indicate that on network lifetime OCoPS outperforms other schemes by over 20% and by over 25% when the coverage rate is higher than 80%. The experimental results also show that our coverage scheme effectively limits the number of on-duty node compared to the other schemes.

A Wireless Actor and Sensor Networks QoS-Aware Routing Protocol for the Emergency Preparedness Class of Applications

Wireless actors and sensor networks (WASNs) can provide a more accurate real time monitoring tool for the emergency preparedness class of application. Quality of service can be an important mechanism to guarantee that the strict requirements for that class of application are met. This paper presents QARP, a QoS-aware routing protocol with service differentiation for WASNs. The publish/subscribe paradigm is used to promote the interaction among the sensor nodes, actor nodes and the sink. The QARP provides low latency and reliable delivery in the presence of failures (with fast subscription of new interests and uniform energy consumption). It uses the less expensive energy path for low priority packets that do not require low latency. A queuing model is used that supports lower transfer rate for lower priority packet delivery in jam conditions. Simulation results show that the protocol is efficient regarding QoS metrics. QARP can be a potential solution for the monitoring of context aware physical environments subject to emergency situations

Network partition-aware geographical data dissemination

Vehicular Ad hoc Networks (VANETs) have attracted the attention of the research community recently as they have opened up a myriad of on the road applications and increased their potential by providing accident-free and intelligent transport systems. The envisaged applications, as well as some inherent VANET characteristics make data dissemination an essential service and a challenging task in these networks. The existing solutions for data dissemination do not effectively address broadcast storm and network partition problems when considered together. To tackle these problems, we propose a novel GEographical Data Dissemination of Alert Information and Aware of Network Partition (GEDDAI-NP), which eliminates the broadcast storm and maximizes data dissemination capabilities across network partitions with short delays and low overhead. The simulation results show that the data dissemination performed by GEDDAI-NP provides better efficiency than other algorithms, outperforming them in different scenarios in all the evaluations carried out.

An energy-aware spatio-temporal correlation mechanism to perform efficient data collection in wireless sensor networks

Large scale dense wireless sensor networks (WSNs) will be increasingly deployed in different classes of applications for accurate monitoring. Due to their high density of nodes, it is very likely that information that is both spatially and temporally correlated can be detected by several nodes what can be exploited to save energy, a key aspect on these networks. Furthermore, it is important to take advantage of these correlations to decrease communication and data exchange. However, current proposals usually result in high delays and outdated data arriving at the sink node. In this work, we go further and propose a new algorithm, called Efficient Data Collection Aware of Spatio-Temporal Correlation (EAST), which uses shortest routes for forwarding the gathered data toward the sink node and fully exploit both spatial and temporal correlations to perform near real-time data collection in WSNs. Simulation results clearly indicate that our proposal can sense an event with a high accuracy of more than 99.7% while still saving the residual energy of the nodes in more than 14 times when compared to the accurate data collection strategy reported in the literature.

A scalable and dynamic data aggregation aware routing protocol for wireless sensor networks

Data aggregation plays an important role in energy constrained wireless sensor networks (WSN). Redundant data can be aggregated at intermediate nodes of a WSN reducing the number of messages exchanged and consequently reducing communication costs. In this work we consider the problem of constructing a dynamic and scalable structure for data aggregation in WSN. Although there are many proposed solutions to data aggregation in WSN, most of them build the data aggregation structure based on the order in which events occur. This kind of structure leads to low quality routing trees and does not address the load balancing problem, since the same tree is used throughout the network life. To tackle these challenges we propose a novel routing protocol called Dynamic and Scalable Tree (DST), which reduces the number of messages necessary to set up a routing tree, maximizes the number of overlapping routes, and selects routes with the highest aggregation rate. The routing tree created by DST does not depend on the order of events and is not held fixed along the occurrence of events. DST was extensively compared with two solutions reported in the literature regarding communication costs, aggregation rate and quality of the routing tree. Results show that the routing tree built by DST provides the best aggregation quality compared with other algorithms outperforming them for different scenarios in all evaluations performed.

Highly Dynamic Routing Protocol for data aggregation in sensor networks

In wireless sensor networks, data aggregation is critical to network lifetime. It implies that data will be aggregated while flowing from multiple sources to a specific node named sink. The construction of routing trees aware of the data aggregation has a considerable cost and solutions in the literature are not efficient for scenarios where the events are of short duration. This paper presents the Dynamic Data-Aggregation Aware Routing Protocol (DDAARP) for wireless sensor networks. This novel protocol builds dynamic routes, which improve the cost and quality of final routing tree. It also reduces the number of messages necessary to set up a routing tree, maximize the number of overlapping routes, selects routes with the highest aggregation rate, and performs reliable data aggregation transmission. DDAARP was compared with two existing solutions reported in the literature regarding communication costs, delivery efficiency and tree quality created. routing tree built by DDAARP has the best quality of aggregation compared with other algorithms. Results show that DDAARP outperforms these solutions for different scenarios in all evaluations performed. Furthermore, it also shows that the proposed algorithm is a good solution for scenarios with short-term events and for events of long duration.

An efficient and robust data dissemination protocol for vehicular ad hoc networks

Vehicular Ad Hoc Networks (VANETs) have emerged as an exciting research and application area. The envisioned applications, as well as some inherent VANET characteristics such as highly dynamic topology, frequently disconnected network, and different and dynamic network density, make data dissemination a challenging task in these networks. Several approaches for data dissemination in VANETs have been recently proposed in the literature. However, more work needs to be done since most of the proposed solutions do not effectively address some or all of the main challenges in these scenarios such as the broadcast storm, network partition and temporal network fragmentation. In this work we consider the broadcast storm problem. To tackle this challenge we propose a novel GEographical Data Dissemination for Alert Information (GEDDAI), which eliminates the broadcast storm and maximizes the capability of performing data dissemination across zones of relevance with low overhead, short delays and high coverage. Simulation results show that the data dissemination performed by GEDDAI provides the best efficiency compared with other algorithms, outperforming them for different scenarios in all performed evaluations.

An energy aware coverage-preserving scheme for wireless sensor networks

How well a large wireless sensor network can be monitored or tracked while keeping long live is a challenging problem known as the energy aware coverage preserving. Several coverage solutions have been introduced based on node scheduling and quality coverage. Node scheduling based solutions usually rely on global clock synchronization and/or time delays to resolve conflicts when determining what nodes should be turned-off to save energy. If these time delays cannot be calculated accurately blind areas might emerge jeopardizing the network coverage quality. Other challenges to node scheduling based solutions include finding optimal wakeup strategies that avoid waking up more nodes than necessary; and keeping connectivity and coverage of the network while optimizing the number of nodes. This paper extends the coverage calculation method proposed by Tian and Georganas, referred here as C-PNSS scheme, and describes a novel distributed solution based on local information exchange without the uncertainty of self-schedule algorithms. A Decision algorithm and a new node wakeup scheme were devised to overcome existing problems in actual schemes. We implement our optimal coverage-preserving scheme (OCoPS) as an extension of LEACH. A set of simulation experiments was performed to evaluate OCoPS performance when compared to LEACH and C-PNSS schemes. The results indicate that our solution outperforms C-PNSS by over 20% on network lifetime and by over 25% on network lifetime when the coverage rate is higher than 80%. LEACH is outperformed by nearly over five times on network lifetime. The experimental results also show that our coverage scheme based on our extended coverage calculation method effectively limits the on-duty node number when compared to both LEACH and C-PNSS.