Using artificial intelligence in routing schemes for wireless networks

For the latest 10 years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well-known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

A new QoS routing algorithm based on self-organizing maps for wireless sensor networks

For the past ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, self-organizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore and compare the performance of two very well known routing paradigms, directed diffusion and Energy- Aware Routing, with our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Giving neurons to sensors. QoS management in wireless sensors networks

Public utilities services (gas, water and electricity) have been traditionally automated with several technologies. The main functions that these technologies must support are AMR, Automated Meter Reading, and SCADA, Supervisory Control And Data Acquisition. Most meter manufacturers provide devices with Bluetoothr or ZigBeeTM communication features. This characteristic has allowed the inclusion of wireless sensor networks (WSN) in these systems. Once WSNs have appeared in such a scenario, real-time AMR and SCADA applications can be developed with low cost. Data must be routed from every meter to a base station. This paper describes the use of a novel QoS-driven routing algorithm, named SIR: Sensor Intelligence Routing, over a network of meters. An arti cial neural network is introduced in every node to manage the routes that data have to follow. The resulting system is named Intelligent Wireless Sensor Network (IWSN)

Giving Neurons to Sensors: An Approach to QoS Management Through Artificial Intelligence in Wireless Networks

For the latest ten years, many authors have focused their investigations in wireless sensor networks. Different researching issues have been extensively developed: power consumption, MAC protocols, selforganizing network algorithms, data-aggregation schemes, routing protocols, QoS management, etc. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed. This paper attempts to encourage the use of artificial intelligence techniques in wireless sensor nodes

Using Artificial Intelligence in Wireless Sensor Routing Protocols

This paper represents a dissertation about how an artificial intelligence technique can be applied to wireless sensor networks. Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded in these kind of networks. However, in some special scenarios the features of neural networks are appropriate to develop complex tasks such as path discovery. In this paper, we explore the performance of two very well known routing paradigms, directed diffusion and Energy-Aware Routing, and our routing algorithm, named SIR, which has the novelty of being based on the introduction of neural networks in every sensor node. Extensive simulations over our wireless sensor network simulator, OLIMPO, have been carried out to study the efficiency of the introduction of neural networks. A comparison of the results obtained with every routing protocol is analyzed

Unified clustering and communication protocol for wireless sensor networks

In this paper we present an energy-efficient cross layer protocol for providing application specific reservations in wireless senor networks called the “Unified Clustering and Communication Protocol ” (UCCP). Our modular cross layered framework satisfies three wireless sensor network requirements, namely, the QoS requirement of heterogeneous applications, energy aware clustering and data forwarding by relay sensor nodes. Our unified design approach is motivated by providing an integrated and viable solution for self organization and end-to-end communication is wireless sensor networks. Dynamic QoS based reservation guarantees are provided using a reservation-based TDMA approach. Our novel energy-efficient clustering approach employs a multi-objective optimization technique based on OR (operations research) practices. We adopt a simple hierarchy in which relay nodes forward data messages from cluster head to the sink, thus eliminating the overheads needed to maintain a routing protocol. Simulation results demonstrate that UCCP provides an energy-efficient and scalable solution to meet the application specific QoS demands in resource constrained sensor nodes. Index Terms — wireless sensor networks, unified communication, optimization, clustering and quality of service

QoS routing in ad-hoc networks using GA and multi-objective optimization

Much work has been done on routing in Ad-hoc networks, but the proposed routing solutions only deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. In this paper, we use Genetic Algorithms (GAs) and multi-objective optimization for QoS routing in Ad-hoc Networks. In order to reduce the search space of GA, we implemented a search space reduction algorithm, which reduces the search space for GAMAN (GA-based routing algorithm for Mobile Ad-hoc Networks) to find a new route. We evaluate the performance of GAMAN by computer simulations and show that GAMAN has better behaviour than GLBR (Genetic Load Balancing Routing).Peer ReviewedPostprint (published version

Polycyclic aromatic hydrocarbons biodegradation using isolated strains under indigenous condition

The treatment and disposal of domestic sIudge is an expensive and environmentally sensitive problem. It is also a growing problem since sludge production will continue to increase as new wastewzter treatment plants are built due to population increase. The large volume of domestic sIudge produced had made it difficult for many countries including Malaysia to assure complete treatment of the sludge before discharging to the receiving environment. Domestic sludge contains diverse range of pollutants such as pathogen, inorganic and organic compounds. These pollutants are toxic, mutagenic or carcinogenic and may threaten human health. Iiilproper disposal and handling of sludge may pose serious impact to the environment especially on soil and water cycles. Previous studies on Malaysian domestic sludge only reported on bulk parameters and heavy metals. Thus, no study reported on organic micro pollutants, namely, polycylic aromatic hydrocarbons (PAHs). Their recalcitrance and persistence make them problematic environmental contaminants. Microbial degradation is considered to be the primary mechanism of PAHs removal from the environment. Much has been reported on biodegradation of PAHs in several countries but there is a lack of information quantitative on this subject in Malaysia. This study is carried out to understand the nature of domestic sludge and to provide a better understanding on the biodegradation processes of PAHs. The methodology of this study comprised field activities, laboratory work and mathematical modelling. Field activities involved sampling of domestic sludge from Kolej Mawar, Universiti Teknologi MARA, Shah Alam, Selangor. Laboratory activities include seven phases of experimental works. First phase is characterization study of domestic sludge based on bulk parameters, heavy metals and PAHs. Second phase is enrichment and purification of bacteria isolated from domestic sludge using single PAHs and mixed PAHs as growth substrate. This was followed by identification of bacteria using BIOLOG system. The fourth phase focussed on turbidity test to monitor growth rate of the isolated bacteria. Preliminary degradation study involves optimization of the process at different substrate concentration, bacteria concentration, pH and temperature. The optimum conditions established from optimization study were used in degradation study. In biodegradation study, two experimental conditions were performed. These conditions include using bacteria isolated from single PAHs as substrate and bacteria isolated from mixed PAHs. Protein and pH tests were done during degradation study. Final activity is mathematical modelling of the biodegradation process. In general results on bulk parameters are comparable to previous studies. Zinc was the main compound with a mean concentration of 11 96.4 mglkg. PAHs were also detected in all of the samples, with total concentration between 0.72 to 5.36 mglkg dry weight for six PAHs. In the examined samples, phenanthrene was the main compound with a mean concentration of 1.0567 mglkg. The results fiom purification studies of bacteria strains sucessfull isolated 13 bacteria strains fiom single PAH substrate while three bacteria were isolated from the mixed PAHs substrate. Based on bacteria growth rates, only six strains grown on single PAHs and three strains grown on mixed PAHs were used for further studies. Results from the optimization study of biodegradation indicated that maximum rate of PAHs removal occurred at 100 mg~-' of PAHs, 10% bacteria concentration, pH 7.0 and 30°C. The results showed that bacteria grown on lower ring of PAHs are not able to grow on higher ring of PAHs. As for example Micrococcus diversus grown on napthalene as sole carbon source was unable to degrade other PAHs like acenapthylene, acenapthene, fluorene, phenanthrene and antlracene. In the case of bacteria isolated from mixed PAHs, the results showed that most of the napthalene was degraded by isolated strains with the highest average degradation rate followed by acenapthylene, acenapthene, fluorene, phenanthrene and anthracene. 377$3(53867$.$$1�781.8�781�$0,1$+ D4ff + c\,cpda~ition trends were observed in the study could be attributed to the different subsr , i,lo\~ir 'Led during isolation process. Interaction through cometabolism and synergistic ocolq bacteria strains isolated from single substrate. Thus, only synergistic interaction was oL, :a 77ed for bacteria isolated from mixed substrate. Corynebacterium urolyticum re\e;;ed I,, be the best strain in degrading PAHs. The experimental results have led to a model conccl~t desclibing I'AHs degradation

SCOR: Software-defined Constrained Optimal Routing Platform for SDN

A Software-defined Constrained Optimal Routing (SCOR) platform is introduced as a Northbound interface in SDN architecture. It is based on constraint programming techniques and is implemented in MiniZinc modelling language. Using constraint programming techniques in this Northbound interface has created an efficient tool for implementing complex Quality of Service routing applications in a few lines of code. The code includes only the problem statement and the solution is found by a general solver program. A routing framework is introduced based on SDN's architecture model which uses SCOR as its Northbound interface and an upper layer of applications implemented in SCOR. Performance of a few implemented routing applications are evaluated in different network topologies, network sizes and various number of concurrent flows.Comment: 19 pages, 11 figures, 11 algorithms, 3 table