On Mobility Management in Multi-Sink Sensor Networks for Geocasting of Queries

In order to efficiently deal with location dependent messages in multi-sink wireless sensor networks (WSNs), it is key that the network informs sinks what geographical area is covered by which sink. The sinks are then able to efficiently route messages which are only valid in particular regions of the deployment. In our previous work (see the 5th and 6th cited documents), we proposed a combined coverage area reporting and geographical routing protocol for location dependent messages, for example, queries that are injected by sinks. In this paper, we study the case where we have static sinks and mobile sensor nodes in the network. To provide up-to-date coverage areas to sinks, we focus on handling node mobility in the network. We discuss what is a better method for updating the routing structure (i.e., routing trees and coverage areas) to handle mobility efficiently: periodic global updates initiated from sinks or local updates triggered by mobile sensors. Simulation results show that local updating perform very well in terms of query delivery ratio. Local updating has a better scalability to increasing network size. It is also more energy efficient than ourpreviously proposed approach, where global updating in networks have medium mobility rate and speed

Activity recognition and tracking system for domestic animals

Ülkemizde dünyada olduğu gibi evcil hayvan sahiplenme oranı gün geçtikçe artmaktadır. Evcil hayvan sahipleri hayvanlarının sağlıklarını takip etmek için çeşitli araçlar ve yöntemler kullanmaktadırlar. Hayvan sağlığının takibi için kullanılan yöntemlerin başında hayvanın hareketlilik seviyesinin gözlemlenmesi gelmektedir. Hareketlik seviyesinde azalma çoğu hayvan hastalığında ilk ve en belirgin semptomlardandır. Bu çalışmada, evcil hayvanların eylemlerinin otomatik olarak tanınması ve takibi için bir Nesnelerin Interneti sistemi geliştirilmiştir. Sistemde evcil hayvanın tasmasına takılan bir sensör düğüm, bu düğümün topladığı verileri bulut mimarisine aktaran bir mobil uygulama ve bulut mimaride verileri otomatik olarak sınıflandıran ve görselleştiren bir yazılım ve arayüz bulunmaktadır. Elde edilen veriler ile evcil hayvanın bir gün içindeki hareketliliği farklı eylem sınıfları (oturma, yürüme, koşma) gösterilerek belirlenmiştir. Çalışmada denek olarak köpek kullanılmıştır.In our country, as in the world, domestic animal ownership rate is increasing day by day. Pet owners use a variety of tools and methods to monitor their animals' health. One of the most commonly used methods to track animal health is to observe animal activity level. A decrease in animal's activity level is the first and most obvious symptom in most animal diseases. In this study, an IoT system is developed to automatically recognize and track the activities of domestic animals. The system includes a sensor node attached to the pet's collar, a mobile application that transfers the data collected by this sensor node to the cloud architecture, and a software and user interface that automatically classifies and visualizes data in the cloud architecture. With the obtained data, the pet's activities within a day were determined by showing different classes of action (sitting, walking, running). Dogs were used as subjects in the study.Publisher's Versio

Detection of DHCP starvation attacks in software defined networks: a case study

Software Defined Networking (SDN) is an emerging concept that maintains and analyzes the network status with its centralized architecture. This facility ensures network operators to monitor and manage the network elements with custom applications running on a single or multiple controllers. In this paper, we show that network security issues such as threat detection can easily be solved by using SDN due to its programmable nature. This paper specifically presents a case study that addresses a solution for detection of DHCP starvation attacks in an SDN, which is one of the most common network security problems that may disable the whole network operations.Publisher's Versio

A virtual infrastructure based on honeycomb tessellation for data dissemination in multi-sink mobile wireless sensor networks

A new category of intelligent sensor network applications emerges where motion is a fundamental characteristic of the system under consideration. In such applications, sensors are attached to vehicles, or people that move around large geographic areas. For instance, in mission critical applications of wireless sensor networks (WSNs), sinks can be associated to first responders. In such scenarios, reliable data dissemination of events is very important, as well as the efficiency in handling the mobility of both sinks and event sources. For this kind of applications, reliability means real-time data delivery with a high data delivery ratio. In this article, we propose a virtual infrastructure and a data dissemination protocol exploiting this infrastructure, which considers dynamic conditions of multiple sinks and sources. The architecture consists of `highways' in a honeycomb tessellation, which are the three main diagonals of the honeycomb where the data flow is directed and event data is cached. The highways act as rendezvous regions of the events and queries. Our protocol, namely hexagonal cell-based data dissemination (HexDD), is fault-tolerant, meaning it can bypass routing holes created by imperfect conditions of wireless communication in the network. We analytically evaluate the communication cost and hot region traffic cost of HexDD and compare it with other approaches. Additionally, with extensive simulations, we evaluate the performance of HexDD in terms of data delivery ratio, latency, and energy consumption. We also analyze the hot spot zones of HexDD and other virtual infrastructure based protocols. To overcome the hot region problem in HexDD, we propose to resize the hot regions and evaluate the performance of this method. Simulation results show that our study significantly reduces overall energy consumption while maintaining comparably high data delivery ratio and low latency

Demo abstract: TeleHealth - Intelligent healthcare with M2M communication module

Chronic diseases, such as diabetes, heart disease (e.g. arrhythmia and hypertension), chronic respiratory diseases (e.g. asthma and COPD), are by far the leading cause of mortality in the world, representing 63% of all deaths. Out of the 36 million people who died from chronic disease in 2008, nine million were under 60. Remote patient monitoring is an efficient and cost-effective solution to mitigate this problem. The key technology to facilitate wireless mobile healthcare or TeleHealth is cellular based M2M (machine-to-machine) communication. In this demo, we present a M2M Communication Module and its healthcare application developed at Turkcell Technology, Applied Research Lab.Publisher's Versio

Noisemap: An environmental noise monitoring sensor network

Çalıştığımız ortamlardaki çevresel gürültünün seviyesi psikolojik ve fiziksel sağlığımız ve iş verimliliği açısından kritik önem taşımaktadır. Bu nedenle çevresel gürültüyü gözlemleyen sistemlere ihtiyaç duyulmaktadır. Bu bildiride, mikrofonlarla donatılmış algılayıcı düğümlerden ve katılımcı akıllı telefonlardan oluşan bir çevresel gürültü izleme ağı kullanılarak, ofis, fabrika gibi kapalı alanların tüm gün boyunca izlenmesine olanak veren bir sistem geliştirilmiştir. Sistem sayesinde çalışma ortamlarından elde edilen ses basınç seviyesi, zaman ve konum bilgileri bulut üzerindeki veri merkezlerine aktarılmış. Elde edilen veriler kullanılarak ortamların çevresel ses haritaları çıkarılmıştır.The environmental noise levels of our working areas have a critical impact on our psychological and physical health and business efficiency. Therefore; there is a need for systems that monitor environmental noise. In this paper, the sensor nodes equipped with microphones and participating smartphones are used to form an environmental noise monitoring network. This system allows monitoring of indoor areas such as offices and factories for the entire day. The sound pressure levels, which are associated with the time and location information, obtained from the work environments through the deployed network are transferred to the cloud. The resulting data are used to create noise maps of the environments.Publisher's Versio