Thomas Pötsch

Influence of future M2M communication on the LTE system

Machine-to-Machine (M2M) communications is one of the latest research areas. This technology aims to enable machines to communicate with each other, mainly, without human intervention. M2M traffic is envisaged to play a big role within the coming years; lots of research projects and standardization bodies around the world have already started paying attention to the rising M2M communication. Current cellular mobile networks, such as LTE, are designed and optimized for traffic characteristics of human-based communication, but M2M traffic is different: Packet sizes are small, but transmitted periodically by numerous endpoints. In this paper, we focus on how LTE cellular networks will handle the massive deployment of M2M devices. In order to do so, the authors specified an M2M traffic model that represent a possible logistical scenario in the future. Besides M2M traffic, also regular LTE traffic is present in the network and the influence of the increasing M2M traffic is investigated. The results of the simulations show that M2M traffic will influence regular, human-based traffic. In particular the file upload time for regular LTE traffic experiences a considerable increase.

Communication techniques and challenges for wireless food quality monitoring

Remote measurement of product core temperature is an important prerequisite to improve the cool chain of food products and reduce losses. This paper examines and shows possible solutions to technical challenges that still hinder practical applications of wireless sensor networks in the field of food transport supervision. The high signal attenuation by water-containing products limits the communication range to less than 0.5 m for the commonly used 2.4 GHz radio chips. By theoretical analysis of the dependency of signal attenuation on the operating frequency, we show that the signal attenuation can be largely reduced by the use of 433 MHz or 866 MHz devices, but forwarding of messages over multiple hops inside a sensor network is mostly unavoidable to guarantee full coverage of a packed container. Communication protocols have to provide compatibility with widely accepted standards for integration into the global Internet, which has been achieved by programming an implementation of the constrained application protocol for wireless sensor nodes and integrating into IPv6-based networks. The sensors battery lifetime can be extended by optimizing communication protocols and by in-network pre-processing of the sensor data. The feasibility of remote freight supervision was demonstrated by our full-scale ‘Intelligent Container’ prototype.

Adaptive Congestion Control for Unpredictable Cellular Networks

Legacy congestion controls including TCP and its variants are known to perform poorly over cellular networks due to highly variable capacities over short time scales, self-inflicted packet delays, and packet losses unrelated to congestion. To cope with these challenges, we present Verus, an end-to-end congestion control protocol that uses delay measurements to react quickly to the capacity changes in cellular networks without explicitly attempting to predict the cellular channel dynamics. The key idea of Verus is to continuously learn a delay profile that captures the relationship between end-to-end packet delay and outstanding window size over short epochs and uses this relationship to increment or decrement the window size based on the observed short-term packet delay variations. While the delay-based control is primarily for congestion avoidance, Verus uses standard TCP features including multiplicative decrease upon packet loss and slow start. Through a combination of simulations, empirical evaluations using cellular network traces, and real-world evaluations against standard TCP flavors and state of the art protocols like Sprout, we show that Verus outperforms these protocols in cellular channels. In comparison to TCP Cubic, Verus achieves an order of magnitude (> 10x) reduction in delay over 3G and LTE networks while achieving comparable throughput (sometimes marginally higher). In comparison to Sprout, Verus achieves up to 30% higher throughput in rapidly changing cellular networks.

Performance Evaluation of CoAP Using RPL and LPL in TinyOS

The use of web services for sensor networking applications is seen as an important part in emerging M2M communications. The Constrained Application Protocol (CoAP) is proposed by the Internet Engineering Task Force (IETF) to optimize the use of the RESTful web service architecture for constrained nodes and networks, for example Wireless Sensor Networks (WSN). In this paper, we present a performance evaluation of the CoAP protocol implemented for the embedded operating system TinyOS. The CoapBlip implementation has been deployed on 20 TelosB motes forming a multi- hop network using the Routing Protocol for Low- power and Lossy Networks (RPL) with the two objective function of MRHOF and OF0. The performance of CoAP has been studied using both objective functions in the routing layer together with having LPL (Low Power Listening) enabled or disabled.

Dissecting Web Latency in Ghana

Web access is prohibitively slow in many developing regions despite substantial effort to increase bandwidth and network penetration. In this paper, we explore the fundamental bottlenecks that cause poor web performance from a clients perspective by carefully dissecting webpage load latency contributors in Ghana. Based on our measurements from 2012 to 2014, we find several interesting issues that arise due to the increasing complexity of web pages and number of server redirections required to completely render the assets of a page. We observe that, rather than bandwidth, the primary bottleneck of web performance in Ghana is the lack of good DNS servers and caching infrastructure. The main bottlenecks are: (a) Recursive DNS query resolutions; (b) HTTP redirections; (c) TLS/SSL handshakes. We experiment with a range of well-known end-to-end latency optimizations and find that simple DNS caching, redirection caching, and the use of SPDY can all yield substantial improvements to user-perceived latency.

Model-driven data acquisition for temperature sensor readings in Wireless Sensor Networks

The increasing interest and utilization of Wireless Sensor Networks has increased the requirements of energy saving for battery powered sensor nodes. Even in modern sensor nodes, communication causes the largest part of energy consumption and therefore ways to reduce the amount of data sending are widely concerned. One solution to reduce data transmission is a model-driven data acquisition technique called Derivative-Based Prediction (DBP). Instead of transmitting every measured sample, a sensor node uses algorithms to compute approximated models to represent the measured data. In this work, we developed an algorithm to monitor temperature samples in different environmental scenarios. We also evaluated the algorithm with regard to its efficiency and classified the recorded temperature patterns to enhance the precision. In our tests, the algorithm successfully suppressed up to 99% of data transmissions while the average error of prediction has been kept below 0.1°C.

Addressing the Challenges of E-Healthcare in Future Mobile Networks

Machine-to-Machine (M2M) communication is expected to play a major role within the coming years towards the development of e-healthcare applications. The design of cellular networks, such as Long Term Evolution (LTE), is optimized to serve the data traffic of human-based communication with broadband requirements. E-healthcare traffic has different characteristics such as small packet sizes, narrowband requirements and huge number of devices. The focus of this work is to investigate the impact of e-healthcare traffic on LTE cellular networks. We develop a possible future scenario of electrocardiography (ECG) devices performing remote monitoring of patients with mobility support in our LTE simulation model. Regular LTE traffic is also deployed in the network and the influence of the varying ECG traffic is examined. The simulation results indicate that the e-healthcare related data traffic has a drastic influence on regular LTE traffic.

xCache: Rethinking Edge Caching for Developing Regions

End-users in emerging markets experience poor web performance due to a combination of three factors: high server response time, limited edge bandwidth and the complexity of web pages. The absence of cloud infrastructure in developing regions and the limited bandwidth experienced by edge nodes constrain the effectiveness of conventional caching solutions for these contexts. This paper describes the design, implementation and deployment of xCache, a cloud-managed Internet caching architecture that aims to proactively profile popular web pages and maintain the liveness of popular content at software defined edge caches to enhance the cache hit rate with minimal bandwidth overhead. xCache uses a Cloud Controller that continuously analyzes active cloud-managed web pages and derives an object-group representation of web pages based on the objects of a page. Using this object-group representation, xCache computes a bandwidth-aware utility measure to derive the most valuable configuration for each edge cache. Our preliminary real-world deployment across university campuses in three developing regions demonstrates its potential compared to conventional caching by improving cache hit rates by about 15%. Our evaluations of xCache have also shown that it can be applied in conjunction with other web optimizations solutions like Shandian, and can improve page load times by more than 50%.

Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

A deeper understanding of interoperability between TinyRPL and ContikiRPL

Today, there exist several standards based and proprietary based protocols that can be used in Wireless Sensor Network (WSN) applications. Proprietary technologies are difficult to integrate into larger networks and currently available Internet-based services. The use of IP based technologies allows easy integration with existing network infrastructure. Interoperability has always been a major concern within the IETF. The previous work has proved that the IPv6 Routing Protocol for Low-power and Lossy Networks (RPL) protocol, proposed by the IETF is interoperable in widely used TinyOS and Contiki platforms. Compared to the previous work, this work highlights the detailed analysis of the behaviour of RPL in these two platforms, in terms of comparison with two objective functions used (MRHOF and OF0), analysis of RPL control messages (DIO, DIS and DAO) and finally the tolerance of RPL performance under varying traffic loads (1 packets per minute to 60 packets per minute). Further, this work gives a detailed insight into implementation specific issues as reasoning for the degradation of the RPL performance, when mixing nodes of TinyOS and Contiki.