Pavle Skocir

Comparison of the CUPUS middleware and MQTT protocol for smart city services

Publish/subscribe messaging pattern is often used as a communication mechanism in data-oriented applications and is becoming wide-spread, especially due to the expansion of the Internet of Things (IoT) services and applications. In addition to MQTT, which is one of the commonly used publish/subscribe protocols in the context of IoT, there are a number of other message queuing solutions, either open or proprietary. We have designed a CloUd-based PUblish/Subscribe (CUPUS) middleware solution within the framework of the FP7 project OpenIoT1 that has developed an open-source cloud platform for the IoT. CUPUS is one of the core OpenIoT components which enables flexible integration of wearable sensors and mobile devices as data sources within the OpenIoT platform. In this paper we compare MQTT and CUPUS in the context of smart city application scenarios. Smart city services pose different key-requirements on IoT publish/subscribe solutions and thus we propose a taxonomy to identify vital features of IoT publish/subscribe middleware. The comparison shows that CUPUS is more appropriate for mobile environments with frequent context changes, while it can filter out unrequired data on devices prior to being reported to backend cloud servers. The MQTT protocol proves to be suitable for Wireless Sensor Networks (WSNs) and heterogeneous environments due to its small code footprint, low bandwidth usage and standardized interfaces. Finally we evaluate the two solutions in terms of message footprint in a real-world scenario, latency and delivery semantics.

Data Filtering in Context-Aware Multi-agent System for Machine-to-Machine Communication

Energy efficiency is an important aspect of Machine-to-Machine (M2M) systems since large number of devices is not connected to unlimited power supply. To tackle this problem, in our context-aware multi-agent system for M2M communication devices are in low-energy mode whenever they do not have any tasks to perform. Context information is exchanged between devices so that each device knows when other devices will be available for communication. On each device in the system, agents are deployed which exchange context information and adjust their wake-up times. In this paper we focus on decreasing energy consumption of M2M Devices which collect measurement data and forward it to back-end system. A filtering algorithm is developed to find repetitive data and to increase the interval for the next transmission. We assumed that when data values are similar to the previously observed values, it is not necessary to forward them to the gateway and back-end system so often. This approach was implemented on Libelium Waspmote devices and showed significant decrease in energy consumption during the period of 24 h.

Quality-of-Service in Machine-to-Machine service provisioning process

This paper tackles the problem of Quality-of-Service (QoS) in heterogeneous Machine-to-Machine (M2M) systems. The concern for QoS guaranties has been widely expressed in the past for both wired and wireless networks. However, only recently when these two types of networks have converged into one, thus making one huge heterogeneous system called M2M, new concerns have emerged. In this paper we measured energy consumption for different communication technologies and proposed an energy consumption model for iOS devices that can be used in future QoS specifications. Finally, we defined a QoS metric that includes both energy and time consumption aspects of one simple M2M service.

Energy consumption model for devices in machine-to-machine system

The paper proposes an energy consumption model for energy constrained devices in Machine-to-Machine communication system. The model specifies generic tasks that are executed on M2M devices. It was implemented on devices on Waspmote and Arduino hardware platforms. Power consumption was calculated for the states of the proposed model. The model with calculated consumption values is applicable for testing algorithms and techniques for achieving higher energy efficiency. Furthermore, the paper presents a basic operating cycle in which tasks from the specified model are executed on M2M devices and M2M gateway in an energy efficient way. Energy consumption during 24 hours by using the suggested operating cycle is compared on Arduino and Waspmote hardware platforms.

User privacy risk calculator

User privacy is becoming an issue on the Internet due to common data breaches and various security threats. Services tend to require private user data in order to provide more personalized content and users are typically unaware of potential risks to their privacy. This paper proposes a risk calculator based on a feedforward neural network that will provide users with an ability to calculate risks to their privacy. The proposed calculator is evaluated on a set of real world example scenarios. Furthermore, to give more insight into privacy issues, each estimated risk is explained by several real life scenarios that might happen if the observed parameters are obtained by an attacker. In turn, this should raise user awareness and knowledge about privacy issues on the Internet.

Data rate fluctuations from user perspective in 4G mobile networks

Approximately two thirds of users worldwide use mobile (i.e. cellular) network for Internet access. Downlink and uplink data rates are important factors for enabling certain level of QoS (Quality of Service) and QoE (Quality of Experience). In this paper the aforementioned data rates were measured using only equipment available to an ordinary subscriber. For Internet access, we used a mobile network technology that currently enables highest data rates - LTE (Long Term Evolution). Two different tools were used for determining the data rates - HAKOMetar and Speedtest. The measurements were carried out on four distinct locations in the city of Zagreb, Croatia and aggregated results are presented separately for weekdays and for weekends. The contribution of our paper is twofold. Firstly, we show how much the data rates fluctuate during the weekdays and weekends, and when maximum uplink and downlink data rates are achieved. Secondly, we compare the measured data rates with those advertised by mobile network operators, and propose the changes they should enforce to better inform mobile network subscribers about the achievable data rates at a certain location.

Communication and Security in Machine-to-Machine Systems

Machine-to-Machine (M2M) systems and technologies currently constitute a hot topic in the field of Information and Communication Technology (ICT), and reflect an increasing need for technologies enabling applications in diverse areas, as well as interactions between continuously increasing numbers of connected devices. Important participants in making M2M systems widely used and applicable in numerous real-life scenarios are standardization organizations. They try to develop technical specifications that address the need for a common M2M service layer, which can be realized through various hardware and software implementations. This chapter presents current standards and architecture of M2M systems with the focus on communication and security issues, while also discussing current and future research efforts addressing important open issues. One of the main problems in the area is correlated with heterogeneous devices, which are using different technologies for communication. Because of communication technology diversity, research challenges are to uniquely identify devices, and to enable them to communicate securely. To tackle the former, previously proposed, a unique identifying scheme that enables device identification regardless of used technology is explained. Regarding the latter, we analyze how current standards and architecture of M2M systems define basic processes for secure connection establishment, and also discuss open issues, both in respect to aspects not covered by current standards and in relation to research proposals which may integrate with M2M systems in future versions of the standards.

Energy efficient task allocation for service provisioning in Machine-to-Machine systems

Machine‐to‐Machine (M2M) communication systems enable autonomous communication between heterogeneous devices. In many applications, those devices are used to obtain measurements from sensors connected to them. By integrating M2M with the Internet of things paradigm, sensors and the data they obtain can be easily accessed via Internet infrastructure. This novelty, along with the advancement of processing power on small devices and the possibility to connect more sensors to one sensing device, poses new challenges and opens new opportunities in the area. This paper presents an algorithm and a protocol devised for task allocation to nodes of the M2M architecture where M2M devices are battery powered. The presented mechanism tackles some of the identified challenges within the area. First challenge is to determine the right node for performing data analysis. Certain data analysis tasks can be performed on device, instead of only on servers, which is a traditional approach. Another challenge is to relate the process of obtaining measurements with user needs, i.e. to collect data only when users have interest in it. The last identified challenge is to extend lifetime of services with higher priority, instead of prolonging lifetime of all devices within the network. Adoption of the proposed mechanism is justified on specific services in a smart home environment. Copyright

Estimating real world privacy risk scenarios

User privacy is becoming an issue on the Internet due to common data breaches and various security threats. Services tend to require private user data in order to provide more personalized content and users are typically unaware of potential risks to their privacy. This paper continues our work on the proposed user privacy risk calculator based on a feedforward neural network. Along with risk estimation, we provide the users with real world example scenarios that depict privacy threats according to selected input parameters. In this paper, we present a model for selecting the most probable real world scenario, presented as a comic, and thus avoid overwhelming the user with lots of information that he/she may find confusing. Most probable scenario estimations are performed by artificial neural network that is trained with real world scenarios and estimated probabilities from real world occurrences. Additionally, we group real world scenarios into categories that are presented to the user as further reading regarding privacy risks.

Activity Detection in Smart Home Environment

Detection of human activities is a set of techniques that can be used in wide range of applications, including smart homes and healthcare. In this paper we focus on activity detection in a smart home environment, more specifically on detecting entrances to a room and exits from a room in a home or office space. This information can be used in applications that control HVAC (heating, ventilation, and air conditioning) and lighting systems, or in Ambient Assisted Living (AAL) applications which monitor the peoples wellbeing. In our approach we use data from two simple sensors, passive infrared sensor (PIR) which monitors presence and hall effect sensor which monitors whether the door is opened or closed. This installation is non-intrusive and quite simple because the sensor node to which sensors are connected is battery powered, and no additional work to ensure power supply needs to be performed. Two approaches for activity detection are proposed, first based on a sliding window, and the other based on artificial neural network (ANN). The algorithms are tested on a dataset collected in our laboratory environment.