Efficient energy use is primarily for any sensor networks to function for a longer time period. There have been many efficient schemes with various progress levels proposed by many researchers. Yet, there still more improvements are needed. This thesis is an attempt to make wireless sensor networks with further efficient on energy usage in the network with respect to rate of delivery of the messages. In sensor network architecture radio, sensing and actuators have influence over the power consumption in the entire network. While listening as well as transmitting, energy is consumed by the radio. However, if by reducing listening times or by reducing the number of messages transmitting would reduce the energy consumption. But, in real time scenario with critical information sensing network leads to information loss. To overcome this an adaptive routing technique should be considered. So, that it focuses on saving energy in a much more sophisticated way without reducing the performance of the sensing network transmitting and receiving functionalities. This thesis tackles on parts of the energy efficiency problem in a wireless sensor network and improving delivery rate of messages. To achieve this a routing technique is proposed. In this method, switching between two routing paths are considered and the switching decision taken by the server based on messages delivered comparative previous time intervals. The goal is to get maximum network life time without degrading the number of messages at the server. In this work some conventional routing methods are considered for implementing an approach. This approach is by implementing a shortest path, Gradient based energy routing algorithm and an observer component to control switching between paths. Further, controlled switching done by observer compared to normal initial switch rule. Evaluations are done in a simulation environment and results show improvement in network lifetime in a much more balanced way.

Der steigende Bedarf an Internettraffic, Speicher und Verarbeitung benötigt immer mehr Hardwareressourcen. Zusätzlich überdimensionieren Datenzentrumbetreiber ihre Infrastruktur, um auch bei Bedarfsspitzen hinreichend Leistung zur Verfügung stellen zu können. Das führt zu einer geringen Ressourcenauslastung und damit zu einem erhöhten Energieverbrauch. Durch Konsolidierung der aktiven Dienste auf einer Teilmenge der physischen Server zu Zeiten geringer Auslastung können zum einen nicht benötigte Server ausgeschaltet werden und zum anderen sind die verbleibenden Server besser ausgelastet. Jedoch müssen sich Dienste nach der Konsolidierung die physischen Ressourcen mit anderen Diensten teilen. Durch Wechselwirkungen auf gemeinsam genutzten Ressourcen, sogenannten Interferenzen, verschlechtert sich die Performanz der Dienste. In dieser Arbeit wird auf Interferenzen eingegangen, die aufgrund des zeitlich variierenden Ressourcenverbrauchs von Diensten entstehen. Am Beispiel von der Rechenzeit einzelner Prozessorkerne wird mit Hilfe des Cutting Stock Problems mit nichtdeterministischen Längen (ND-CSP) der Energieverbrauch durch die Zahl der benötigten Ressourcen um bis zu 64,1% gesenkt. Durch Berücksichtigung der zeitlichen Variation des Ressourcenverbrauchs verbessert sich die Performanz um bis zu 59,6% gegenüber anderen Konsolidierungsstrategien. Außerdem wird das Konzept des Überlappungskoeffizienten eingeführt. Dieser beschreibt die probabilistische Beziehung zweier parallel laufender Dienste, inwiefern sie gleichzeitig aktiv sind. Sind Dienste nicht gleichzeitig aktiv, können sie ohne zu erwartende Interferenzen konsolidiert werden. Umgekehrt sollte die Konsolidierung gleichzeitig aktiver Dienste vermieden werden. Die Analyse eines Datenzentrums von Google zeigt, dass beide Szenarien einen signifikanten Anteil darstellen. Zur Berücksichtigung des Überlappungskoeffizienten wird das ND-CSP erweitert und näherungsweise gelöst. Hier zeigt sich jedoch weder eine Verbesserung noch eine Verschlechterung der Performanz der Dienste bei gleichem Energieverbrauch. Perspektivisch, bei der exakten Lösung und weiterer Optimierung, können aber damit Dienste eventuell so allokiert werden, dass ihre Interferenzen reduziert oder im Idealfall sogar weitgehend ausgeschlossen werden können. / An increasing portion of IP traffic is processed and stored in data centers. However, data center providers tend to over-provision their resources. Therefore, underutilized resources unnecessarily waste energy. Consolidating services allows them to be executed within a subset of the entire data center and to turn off the unnecessary, idling machines. Additionally, the remaining machines are properly utilized and, hence, more energy-efficient. Nevertheless, this has to be balanced against degrading the quality of service due to the shared resources of the physical machines after the consolidation. This thesis focuses on the above mentioned interferences due to fluctuating workloads. These are treated in the framework of the Cutting Stock Problem, where items with non-deterministic length are introduced. This reduces the power consumption by minimizing the necessary, active resources by up to 64.1% for the exemplary CPU time of individual cores. Thanks to the awareness of workload fluctuations, it improves the performance of services by up to 59.6% compared to other allocation schemes. Additionally, the concept of 'overlap coefficients' is introduced, which describes the probabilistic relation between two services which run in parallel. The more often these services are active at the same time the higher the overlap coefficient and vice versa. Services which are not active at the same time can be consolidated without any expected interference effects, while these with common activity periods should not be consolidated. The analysis of one of Google's data centers unveils that most of the services can be mapped onto one of the two patterns, while few with undetermined relation remain. The ND-CSP is extended by the 'overlap coefficient' and approximatively solved. In contrast to the former ND-CSP, neither an improvement nor a deterioration of the consolidation results is obtained. In the future, the services can be allocated with reduced or even without interference effects if an exact solution or a multi-objective optimization is applied.

Efficient energy use is primarily for any sensor networks to function for a longer time period. There have been many efficient schemes with various progress levels proposed by many researchers. Yet, there still more improvements are needed. This thesis is an attempt to make wireless sensor networks with further efficient on energy usage in the network with respect to rate of delivery of the messages. In sensor network architecture radio, sensing and actuators have influence over the power consumption in the entire network. While listening as well as transmitting, energy is consumed by the radio. However, if by reducing listening times or by reducing the number of messages transmitting would reduce the energy consumption. But, in real time scenario with critical information sensing network leads to information loss. To overcome this an adaptive routing technique should be considered. So, that it focuses on saving energy in a much more sophisticated way without reducing the performance of the sensing network transmitting and receiving functionalities. This thesis tackles on parts of the energy efficiency problem in a wireless sensor network and improving delivery rate of messages. To achieve this a routing technique is proposed. In this method, switching between two routing paths are considered and the switching decision taken by the server based on messages delivered comparative previous time intervals. The goal is to get maximum network life time without degrading the number of messages at the server. In this work some conventional routing methods are considered for implementing an approach. This approach is by implementing a shortest path, Gradient based energy routing algorithm and an observer component to control switching between paths. Further, controlled switching done by observer compared to normal initial switch rule. Evaluations are done in a simulation environment and results show improvement in network lifetime in a much more balanced way.