Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of co verage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality

Estimation and Improvements of the Fundamental QoS in Networks with Random Topologies

The computer communication paradigm is moving towards the ubiquitous computing and Internet of Things (IoT). Small autonomous wirelessly networked devices are becoming more and more present in monitoring and automation of every human interaction with the environment, as well as in collecting various other information from the physical world. Applications, such as remote health monitoring, intelligent homes, early fire, volcano, and earthquake detection, traffic congestion prevention etc., are already present and all share the similar networking philosophy. An additional challenging for the scientific and engineering world is the appropriateness of the alike networks which are to be deployed in the inaccessible regions. These scenarios are typical in environmental and habitat monitoring and in military surveillance. Due to the environmental conditions, these networks can often only be deployed in some quasi-random way. This makes the application design challenging in the sense of coverage, connectivity, network lifetime and data dissemination. For the densely deployed networks, the random geometric graphs are often used to model the networking topology. This paper surveys some of the most important approaches and possibilities in modeling and improvement of coverage and connectivity in randomly deployed networks, with an accent on using the mobility in improving the network functionality

Permission-based Privacy Analysis for Android Applications

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety mostly relies on the features like rating and popularity, rather than in understanding context of listed permissions. In this paper we investigate the relationship between the features collected from Android Market API 23 (such as Popularity, Total Number of Permissions, Number of Dangerous Permissions, Rating and Package Size) to app’s privacy violation. To show the influence of each feature we use linear regression and R squared statistics. The conducted research can contribute to the classification of mobile applications with regards to the threat on user’s privacy

Implementation of the AODV Routing in an Energy-constrained Mesh Network

Wireless sensor networks (WSNs) compose the fundamental platform for a number of Internet of Things (IoT) applications, especially those related to the environmental, health, and military surveillance. While being autonomous in power supply, the main challenge in node’s processing and communication architecture design remains the energy efficiency. However, this goal should not limit the main functionality of the system which is often related to the network coverage and connectivity. This paper shows the implementation of the Ad-hoc On-demand Distance Vector (AODV) routing algorithm in an XBee based platform. As shown, the network can achieve low power consumption per node primarily due to the energy efficiency of the wireless transceivers and the due to the capability of the firmware to enable different operation modes. On the other hand, while inheriting the advantages of flooding-based route discovery protocols, the implemented AODV algorithm further minimizes the data and processing overhead, which implies the additional lifetime prolongation of the energy-constrained mesh network

Implementation of the AODV Routing in an Energy-constrained Mesh Network

Wireless sensor networks (WSNs) compose the fundamental platform for a number of Internet of Things (IoT) applications, especially those related to the environmental, health, and military surveillance. While being autonomous in power supply, the main challenge in node’s processing and communication architecture design remains the energy efficiency. However, this goal should not limit the main functionality of the system which is often related to the network coverage and connectivity. This paper shows the implementation of the Ad-hoc On-demand Distance Vector (AODV) routing algorithm in an XBee based platform. As shown, the network can achieve low power consumption per node primarily due to the energy efficiency of the wireless transceivers and the due to the capability of the firmware to enable different operation modes. On the other hand, while inheriting the advantages of flooding-based route discovery protocols, the implemented AODV algorithm further minimizes the data and processing overhead, which implies the additional lifetime prolongation of the energy-constrained mesh network

Permission-based Privacy Analysis for Android Applications

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety mostly relies on the features like rating and popularity, rather than in understanding context of listed permissions. In this paper we investigate the relationship between the features collected from Android Market API 23 (such as Popularity, Total Number of Permissions, Number of Dangerous Permissions, Rating and Package Size) to app’s privacy violation. To show the influence of each feature we use linear regression and R squared statistics. The conducted research can contribute to the classification of mobile applications with regards to the threat on user’s privacy

A Review on the Emerging Technologies for Air Pollution Monitoring and Management

Air pollution (AP) is one of the main causes of lung cancer and stroke. In order to minimize the negative health impacts, AP should be properly moni- tored and managed. Conventional systems are expensive and sparsely deployed. As such, they cannot provide the required spatiotemporal resolution. This paper reviews the emerging technologies for real-time AP monitoring based on Wire- less Sensor Networks (WSNs). The review is focused on data acquisition and dissemination, as well as on the design and implementation issues. The role of Machine Learning (ML) in AP monitoring and management is also considered

TCP Congestion Control Mechanisms – an Experimental Analysis and Comparison

The incompatibility between traffic load and network processing/communication capacities brings networks to the congestion state. This typically results in the overall network performance deterioration. Various approaches to congestion control have been proposed so far, both at the network and transport layer of networking architecture. However, there is still no such an algorithm that would overperform all the other algorithms in all of the networking scenarios. This study aims to analyze and compare the most popular traditional TCP approaches to congestion control. New Reno, Cubic, and modified SACK TCP were deployed in an OPNET- based simulated topology with varying packet delays and packet loss rate. Although expected (to some extent), SACK version has shown better performances in networks with lower packet delays. Cubic, however, performed surprisingly under the expectations as compared to two other versions, while New Reno has shown consistency along various different scenarios and implementations

IoT Solution: A Mobile Application for Public Transport QoE Improvement

Public transportation in Kosovo has shown to have frequent delays. The delay intervals can be unpredictable, especially in busy hours and regarding the intercity lines. So far, not a substantial effort has been done in order to improve the system’s performance. This paper presents an Internet of Things (IoT) solution for improving the public transport Quality of Experience (QoE). The main goal of the proposed information system is to remotely (and precisely) inform the citizens on real arrival times of the busses at respective stations. Through GPS localization and GSM/3G connectivity, the system enables for web based real time bus tracking. From their smart phones, users can select a specific bus line, and can be visually (on the map) informed on the position of the bus at any time. The arrival time at specific station is also estimated. The system has been tested in public transport in the city of Prishtina and the test results have confirmed its functionality and applicability. Besides its main goal that is focused on the user’s experience, we expect for the data collected from the system to be used in improving the overall public transport system quality in Kosov