Omnet++ Research Papers

We explore the risks to security and privacy in IoT networks by setting up an inexpensive home automation network and performing a set of experiments intended to study attacks and defenses. We focus on privacy preservation in home automation networks but our insights can extend to other IoT applications. Privacy preservation is fundamental to achieving the promise of IoT, Industrial Internet and M2M.

We look at both simple cryptographic techniques and information manipulation to protect a user against an adversary inside the IoT network or an adversary that has compromised remote servers. We show how user data can be masked or selectively leaked and manipulated. We provide a blueprint for inexpensive study of IoT security and privacy using COTS products and services.

The trend of using location-based services (LBS) is not new but has evolved over long time and continues to enter into new application and service landscapes. LBS have essentially targeted outdoor scenarios, whereas GPS is the defacto standard for these cases. Indoor localization technologies are also gaining attraction.

In this paper, we present our Linux-based solution, which runs on low-cost embedded hardware, and is equipped with shortrange wireless technologies such as Bluetooth and WIFI. Using the beaconing capabilities of these technologies in combination with control over M2Mprotocols, we are able provide different applications at the point of presence (PoP).

To implement cutting-edge services such as high-resolution movie streaming and smart metering on mobile networks cost-effectively, mobile operators must meet various conflicting requirements. For example, they must manage a massive number of devices in smart-meter-type machine-to-machine (M2M) applications for which quality-of-service (QoS) requirements are quite lenient. At the same time, they need to support stringent QoS requirements in the form of a few milliseconds of delay and a high bandwidth guarantee for a smaller number of devices in video and remote surgery applications. As building a dedicated per-service physical network is very costly, network slicing by means of resource virtualization was developed to accommodate such heterogeneous services in a single physical network infrastructure. In network slicing, network resources are isolated to form slices, which then can be used to provide different services.

This slicing is helpful in accommodating conflicting, often incompatible services at the cost of losing the multiplexing gain achieved in monolithic composite service networks. The loss in multiplexing gain is not a big problem when the number of slices is relatively low. However, numerous services are provided in cellular networks, and the number is expected to be drastically higher in the 5G era. Creating per-service slices would lead to wastage of resources. In this regard, we aim at balancing the need for isolation to meet conflicting service requirements against resource usage efficiency. We investigated possible means of simultaneously achieving isolation and minimizing the loss of multiplexing gain. Our findings will aid in the development of network management architecture suitable for the 5G era and beyond.

Unmanned Aerial Vehicles (UAV) have several uses in civilians and military applications, such as search and rescue missions, cartography and terrain exploration, industrial plant control, surveillance, public security, firefight, and others. Swarms of UAVs may further increase the effectiveness of these tasks, since they enable larger coverage, more accurate or redundant sensed data, fault tolerance, etc. Swarms of aerial robots require real-time coordination, which is just a specific case of M2Mcollaboration. But one of the biggest challenges of UAV swarming is that this real-time coordination has to happen in a wide-area setting where it is expensive, or even impossible, to set up a dedicated wireless infrastructure for this purpose.

Instead, one has to resort to conventional 3G/4G wireless networks, where communication latencies are in the range of 50-150 ms. In this paper we tackle the problem of UAV swarm formation and maintenance in areas covered by such mobile network, and propose a bandwidth-efficient multi-robot coordination algorithm for these settings. The coordination algorithm was implemented on the top of our mobile middle ware SDDL, uses its group-cast communication capability, and was tested with simulated UAVs.

Long Term Evolution (LTE) is an attractive infrastructure for Smart Grid (SG) networks because it provides high bandwidth and low latency over a large coverage area. Although LTE networks are primary designed for Human-to-Human (H2H) communication, SG networks primarily involve Machine-to-Machine (M2M) communications. One such SG network component is the Smart Meter (SM), which utilizes M2M communications to report power consumption to a centralized control center at periodic intervals. As defined by the LTE standard, all User Equipment (UE), including SMs, need to make a connection to transmit a packet. That means, UEs need a scheduling and resource blocks (RBs).

In this paper, we introduce SM packet transmission via LTE control signaling in order to conserve resources at the eNode-B such as physical channels, scheduling and RBs. Heavy and medium load are compared to investigate packet loss at the eNode-B. With our proposed mechanism, results show that SM packets can be sent via a control signal with no scheduling or RB usage required at the eNode-B. Simulation results show that usage of the Physical Uplink Share CHannel (PUSCH), Physical Downlink Control CHannel (PDCCH), and Physical Downlink Share CHannel (PDSCH) are reduced by 2%. In addition, packets loss during heavy load at the eNode-B is decreased by 15% when compared with the LTE standard.

Video content currently makes up nearly half of the “fixed” Internet traffic and more than a third of the mobile traffic in North America, with most other regions showing similar trends. As mobile data rates continue to increase and more people rely on 802.11 wireless for home and commercial Internet access, the amount of video transmitted over at least one wireless hop will likely continue to increase.

In addition, as cameras continue to become smaller and cheaper, the demand for video services in sensor and MANET networks will also increase. In this paper, we examine the state of the art of wireless video communication at each layer of the networking stack. We consider both existing and emerging technologies at each layer of the protocol stack as well as cross-layer designs, and discuss how these solutions can increase the video experience for the end user.

Online micro blogging has been very popular in today’s Internet, where users follow other people they are interested in and exchange information between themselves. Among these exchanges, video links are a representative type on a micro blogging site. The impact is fundamental-not only are viewers in a video service directly coming from the micro blog sharing and recommendation, but also are the users in the micro blogging site representing a promising sample to all the viewers. It is intriguing to study a proactive service deployment for such videos, using the propagation patterns of micro blogs.

Based on extensive traces from Youku and Tencent Weibo, a popular video sharing site and a favored micro blogging system, we explore how video propagation patterns in the micro blogging system are correlated with video popularity on the video sharing site. Using influential factors summarized from the measurement studies, we further design a neural network-based learning framework to predict the number of potential viewers and their geographic distribution. We then design proactive video deployment algorithms based on the prediction framework, which not only determines the upload capacities of servers in different regions, but also strategically replicates videos to these regions to serve users. Our Planet Lab-based experiments verify the effectiveness of our design.

Optimizing cloud gaming experience is no easy task due to the complex trade-off between gamer quality of experience (QoE) and provider net profit. We tackle the challenge and study an optimization problem to maximize the cloud gaming provider’s total profit while achieving just-good-enough QoE. We conduct measurement studies to derive the QoE and performance models. We formulate and optimally solve the problem. The optimization problem has exponential running time, and we develop an efficient heuristic algorithm. We also present an alternative formulation and algorithms for closed cloud gaming services with dedicated infrastructures, where the profit is not a concern and overall gaming QoE needs to be maximized.

We present a prototype system and test bed using off-the-shelf virtualization software, to demonstrate the practicality and efficiency of our algorithms. Our experience on realizing the test bed sheds some lights on how cloud gaming providers may build up their own profitable services. Last, we conduct extensive trace-driven simulations to evaluate our proposed algorithms. The simulation results show that the proposed heuristic algorithms: (i) produce close-to-optimal solutions, (ii) scale to large cloud gaming services with 20,000 servers and 40,000 gamers, and (iii) outperform the state-of-the-art placement heuristic, e.g., by up to 3.5 times in terms of net profits.

This paper presents a novel smart down-link scheduling scheme to enhance the performance of multimedia transmission over LTE (Long Term Evolution) networks. LTE represents a promising framework for next generation broadband multimedia services because of its significantly increased data rate over 3G cellular networks. However, the current LTE scheduling scheme has been designed largely for general data traffic without adequate consideration of multimedia characteristics. Moreover, the “hard” hand-off (HO) procedure adopted in LTE will further degrade the multimedia services when the mobile user moves from one cell to another. Even with increased data rate, current LTE systems still cannot meet the expected quality-of-service (QoS) to the mobile users under various mobility scenarios, especially when the hard HO is evoked. Aiming at overcoming these major challenges, we develop in this research a QoS-driven smart down-link scheduling scheme for enhanced multimedia transmission over LTE network.

The proposed design shall consider the following QoS metrics: 1) The delay constraint of voice-over-IP (VoIP) flow; 2) The packet deadline of video flow; 3) The service degradation induced by hard HO procedure. We achieve the design objectives by creating three QoS driven operational control modules: a transmission delay control module to ensure the on-time arrival of various types of multimedia data, a HO control module to warrant continuous multimedia services when the user moves across a cell boundary, and a resource allocation module to strategically map the requested flows to best-fit radio resource blocks. Simulation results confirm the performance gain of the proposed scheme.

Mobile devices are increasingly used as terminals for playback of multimedia content. However, maximizing the user’s quality of experience is challenging due to the highly variable conditions of the wireless channels. A possibility to cope with such a variability is to dynamically adapt the source coding rate during the transmission, which is the underlying idea of the DASH standard. This work proposes a new framework to improve the quality of the DASH-based streaming experience by allowing to adjust the trade-off between the quality of received content and the risk of playback freeze due to an empty buffer, which is a strong quality-disruptive event.

The problem is analytically formulated and an efficient method to compute the playback freeze probability as a function of the representation choices over time is presented. Numerous simulation results using real download rate traces of 3G channels show the performance improvement compared to other bandwidth-adaptive algorithms as well as the robustness of the framework to variations of its most important parameters.