Abstract—Opportunistic Routing (OR) is a novel routing technique for wireless mesh networks that exploits the broadcast nature of the wireless medium. OR combines frames from multiple receivers and therefore creates a form of Spatial Diversity, called MAC Diversity [1]. The gain from OR is especially high in networks where the majority of links has a high packet loss probability. The updated IEEE S02.11n standard improves the physical layer with the ability to use multiple transmit and receive antennas, i.e. Multiple-Input and Multiple-Output (MIMO), and therefore already offers spatial diversity on the physical layer, i.e. called Physical Diversity, which improves the reliability of a wireless link by reducing its error rate. In this paper we quantify the gain from MAC diversity as utilized by OR in the presence of PHY diversity as provided by a MIMO system like S02.11n. We experimented with an IEEE S02.11n indoor testbed and analyzed the nature of packet losses. Our experiment results show negligible MAC diversity gains for both interference-prone 2.4 GHz and interference-free 5 GHz channels when using 802.11n. This is different to the observations made with single antenna systems based on 802.11b/g [1], as well as in initial studies with S02.11n [2].

Keywords—IEEE 802.11n , MAC Diversity , Opportunistic Routing , PHY Diversity , Research , Testbed , Wireless Networks

@inproceedings{DBLP:conf/wd/ZubowSS12,
  author    = {Anatolij Zubow and
               Robert Sombrutzki and
               Markus Scheidgen},
  title     = {MAC diversity in IEEE 802.11n MIMO networks},
  booktitle = {Wireless Days},
  year      = {2012},
  pages     = {1-8},
  ee        = {http://dx.doi.org/10.1109/WD.2012.6402802},
  crossref  = {DBLP:conf/wd/2012},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/wd/2012,
  title     = {Proceedings of the IFIP Wireless Days Conference 2012,n,
               Ireland, November 21-23, 2012},
  booktitle = {Wireless Days},
  publisher = {IEEE},
  year      = {2012},
  isbn      = {978-1-4673-4402-9},
  ee        = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6387977},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract—Map/Reduce is the programming model in cloud computing. It enables the processing of data sets of unprecedented size, but it also delegates the handling of complex data structures completely to its users. In this paper, we apply Map/Reduce to EMF-based models to cope with complex data structures in the familiar an easy-to-use and type-safe EMF fashion, combining the advantages of both technologies. We use our framework EMF-Fragments to store very large EMF models in distributed key-value stores (Hadoop’s Hbase). This allows us to build Map/Reduce programs that use EMF’s generated APIs to process those very large EMF-models. We present our framework and two example Map/Reduce jobs for querying software models and for analyzing sensor data represented as EMF-models.

Keywords—EMF, big data, cloud computing, map/reduce, meta-modeling

 @inproceedings{Scheidgen:2012:MEM:2446224.2446231,
 author = {Scheidgen, Markus and Zubow, Anatolij},
 title = {Map/reduce on EMF models},
 booktitle = {Proceedings of the 1st International Workshop on Model-Driven Engineering for High Performance and CLoud computing},
 series = {MDHPCL '12},
 year = {2012},
 isbn = {978-1-4503-1810-5},
 location = {Innsbruck, Austria},
 pages = {7:1--7:5},
 articleno = {7},
 numpages = {5},
 url = {http://doi.acm.org/10.1145/2446224.2446231},
 doi = {10.1145/2446224.2446231},
 acmid = {2446231},
 publisher = {ACM},
 address = {New York, NY, USA},
 keywords = {EMF, big data, cloud computing, map/reduce, meta-modeling},
}

Abstract—Current Wireless Sensor Networks (WSN) consist of low powered energy efficient nodes with short range radios and limited computation capabilities. Sensing applications with multiple sensors, high sample rates, and large spatial coverage are not realizable with conventional WSNs. We propose High Performance WSNs (HP-WSN) with an 802.11n based physical layer and opportunistic routing to overcome the limitations of existing WSNs. We present a research test-bed for such HP-WSNs. As an intermediate step towards actual HP-WSNs, our test-bed (HWL) collects raw data into a centralized data store to provide an experiment friendly environment. The collected raw data includes sensor data (to develop new sensing applications) and data about network and system operation (to develop the sensor network). We provide an example HP-WSN application, derive research objectives for the development of HP-WSNs, provide a test-bed architecture and present evaluation results on network and data storage performance to show the principle feasibility of HP-WSNs.

Keywords—Databases; IEEE 802.11n Standard; Routing protocols; Wireless Sensor Networks; Test-Bed

@INPROCEEDINGS{6240552, 
author={Scheidgen, M. and Zubow, A. and Sombrutzki, R.}, 
booktitle={Networked Sensing Systems (INSS), 2012 Ninth International Conference on}, 
title={HWL #x2014; A high performance wireless sensor research network}, 
year={June}, 
pages={1-4}, 
keywords={Databases;IEEE 802.11n Standard;Routing;Routing protocols;Sensors;Wireless communication;Wireless sensor networks;IEEE 802.11n;Opportunistic Routing;Research Testbed;Wireless Sensor Networks}, 
doi={10.1109/INSS.2012.6240552}
}

Abstract—In this paper, we present the Smart Berlin Testbed as an infrastructure for experimental research on Smart City scenarios. As part of Smart Cities, applications will arise that build upon a variety of information sources and provide the user with near real-time information about the surrounding environment. An important role in this scenarios will be taken by wireless network infrastructures. They will function as interfaces to the users who connect with their smartphone or laptop to access the applications. Additionally, wireless and wired sensor networks are required to monitor the urban environment. The Smart City infrastructure needs to integrate these sensor networks and make them accessible and controllable for the applications. The set-up of the Smart Berlin Testbed is accomplished with the interconnection of two large wireless mesh and sensor networks in Berlin, namely the DES-Testbed at the Freie Universität Berlin and the HWL-Testbed at the Humboldt University Berlin. Together, both networks comprise 250 wireless multi-radio mesh routers and an amount of heterogeneous sensor nodes in the same order. We describe how we interconnect the testbeds via the Internet and the provided research possibilities resulting from the diverse network architectures. As a first experiment, we show results of a white space detection experiment that has been carried out in the Smart Berlin Testbed in order to assess the channel conditions at the testbed sites.

Keywords—smart city, wireless sensor networks, wireless mesh networks

@inproceedings{DBLP:conf/lcn/JuraschekZHSBSGF12,
  author    = {Felix Juraschek and
               Anatolij Zubow and
               Oliver Hahm and
               Markus Scheidgen and
               Bastian Blywis and
               Robert Sombrutzki and
               Mesut G{\"u}nes and
               Joachim Fischer},
  title     = {Towards Smart Berlin - an experimental facility for heterogeneous
               Smart City infrastructures},
  booktitle = {LCN Workshops},
  year      = {2012},
  pages     = {886-892},
  ee        = {http://dx.doi.org/10.1109/LCNW.2012.6424078},
  crossref  = {DBLP:conf/lcn/2012w},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/lcn/2012w,
  title     = {37th Annual IEEE Conference on Local Computer Networks,
               Workshop Proceedings, Clearwater Beach, FL, USA, October
               22-25, 2012},
  booktitle = {LCN Workshops},
  publisher = {IEEE},
  year      = {2012},
  isbn      = {978-1-4673-2130-3},
  ee        = {http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6415465},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract—Smart cities use networks of sensors, actuators, and centralized computing clusters to observe physical reality, derive information, and thereby influence citizens and authorities. Smart city applications therefore require three components to work: wireless sensor networks, geo-information systems, and frameworks for distributed analysis of sensor and geo-data. In this paper, we provide an overview on a set of concrete technologies for such information and communication infrastructures for smart cities. These technologies include a combination of WiFi- and PAN-based sensor networks, City GML data, a model-driven approach to collect and manage data, as well as distributed data analysis based on domain specific languages. We show how we use these technologies to research two typical smart city applications: earthquake early warning and traffic surveillance.

Keywords—smart city, wireless sensor networks, traffic management

@inproceedings{DBLP:conf/sam/FischerRSSGNWSZESJ12,
  author    = {Joachim Fischer and
               Jens-Peter Redlich and
               Bj{\"o}rn Scheuermann and
               Jochen H. Schiller and
               Mesut G{\"u}nes and
               Kai Nagel and
               Peter Wagner and
               Markus Scheidgen and
               Anatolij Zubow and
               Ingmar Eveslage and
               Robert Sombrutzki and
               Felix Juraschek},
  title     = {From Earthquake Detection to Traffic Surveillance - About
               Information and Communication Infrastructures for Smart
               Cities},
  booktitle = {SAM},
  year      = {2012},
  pages     = {121-141},
  ee        = {http://dx.doi.org/10.1007/978-3-642-36757-1_8},
  crossref  = {DBLP:conf/sam/2012},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/sam/2012,
  editor    = {{\O}ystein Haugen and
               Rick Reed and
               Reinhard Gotzhein},
  title     = {System Analysis and Modeling: Theory and Practice - 7th
               International Workshop, SAM 2012, Innsbruck, Austria, October
               1-2, 2012. Revised Selected Papers},
  booktitle = {SAM},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {7744},
  year      = {2013},
  isbn      = {978-3-642-36756-4},
  ee        = {http://dx.doi.org/10.1007/978-3-642-36757-1},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract—It is hard to experiment with test-beds for communi- cation networks: data produced in the network has to be retrieved and analyzed, networks must be reconfigured before and between experiments, data is often little structured (log-files) and analysis methods and tools are generic. Even though many problems of experimentation are the same for all experiments, re-use is sparse and even simple experiments require large efforts.

We present a framework that attempts to solve these problems: we define a set of requirements for experimenting with network test-beds, we describe the principles and inner workings of our framework, demonstrate it with a typical example experiment, and present measurement results that illustrate the feasibility and scalability of our approach. Some qualitative and quantitative aspects of ClickWatch are compared to the commonly used log- file based approach to experimentation.

Keywords—meta-modeling, model-persistence, EMF, big-data, cloud, map-reduce

@inproceedings{DBLP:conf/models/ScheidgenZFK12,
  author    = {Markus Scheidgen and
               Anatolij Zubow and
               Joachim Fischer and
               Thomas H. Kolbe},
  title     = {Automated and Transparent Model Fragmentation for Persisting
               Large Models},
  booktitle = {MoDELS},
  year      = {2012},
  pages     = {102-118},
  ee        = {http://dx.doi.org/10.1007/978-3-642-33666-9_8},
  crossref  = {DBLP:conf/models/2012},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

@proceedings{DBLP:conf/models/2012,
  editor    = {Robert B. France and
               J{\"u}rgen Kazmeier and
               Ruth Breu and
               Colin Atkinson},
  title     = {Model Driven Engineering Languages and Systems - 15th International
               Conference, MODELS 2012, Innsbruck, Austria, September 30-October
               5, 2012. Proceedings},
  booktitle = {MoDELS},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {7590},
  year      = {2012},
  isbn      = {978-3-642-33665-2},
  ee        = {http://dx.doi.org/10.1007/978-3-642-33666-9},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract: Opportunistic Routing (OR) is a novel routing technique for wireless mesh networks that exploits the broadcast nature of the wireless medium. OR combines frames from multiple receivers and therefore creates a form of Spatial Diversity, called MAC Diversity. The gain from OR is especially high in networks where the majority of links has a high packet loss probability. The updated IEEE 802.11n standard improves the physical layer with the ability to use multiple transmit and receive antennas, i.e. Multiple-Input and Multiple-Output (MIMO), and therefore already offers spatial diversity on the physical layer, i.e. called Physical Diversity, which improves the reliability of a wireless link by reducing its error rate. In this paper we quantify the gain from MAC diversity as utilized by OR in the presence of PHY diversity as provided by a MIMO system like 802.11n. We experimented with an IEEE 802.11n indoor testbed and analyzed the nature of packet losses. Our experiment results show negligible MAC diversity gains for both interference-prone 2.4 GHz and interference-free 5 GHz channels when using 802.11n. This is different to the observations made with single antenna systems based on 802.11b/g, as well as in initial studies with 802.11n.

Download full paper here

@article{DBLP:journals/corr/abs-1203-2041,
  author    = {Anatolij Zubow and
               Robert Sombrutzki and
               Markus Scheidgen},
  title     = {Towards MAC/Anycast Diversity in IEEE 802.11n MIMO Networks},
  journal   = {CoRR},
  volume    = {abs/1203.2041},
  year      = {2012},
  ee        = {http://arxiv.org/abs/1203.2041},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}