Deployment of Wireless Mesh Networks

In a previous blog post describing the basic components of a WMN, we highlight  that the  network performance depends mainly on the design issue. In what follows we will detail how to deal with the deployment of WMN in general and specially in the case of the Carmesh project. This latter problem  consists mainly of treating the two following problems:

  • Where the mesh routers have to be placed?
  • How to connect the mesh routers among them to form a balanced backbone topology?

First, the mesh nodes placement problem is related to the access tier design issue, which aims at achieving the following objectives:

  1. Minimizing the installation cost: This objective can be achieved by reducing the number of mesh routers necessary to provide the target wireless coverage.
  2. Coverage optimization: The mesh router positions are determined based on available maps or drawings and according to the required quality of service expressed in terms of Signal to Interference Noise Ratio (SINR).
  3. Minimize the interference effect: To fulfil this objective, we have to ensure that the frequency channels assigned to the access radio interfaces are orthogonal (or sufficiently non-intereferring) to ultimately increase the nominal data rate for each user.

Second, the mesh nodes logical connections strategy deals with forming the backhaul network and its objectives can be summarized as follows:

  1. Backhaul network connectivity: Selecting the links connecting mesh routers among them.
  2. Maximizing the backhaul network capacity: Exploiting the overall backhaul network capacity.

The access network design problem can be solved first using the set covering problem to determine the minimum number of mesh routers required to cover all users. The coverage criterion is expressed as the signal strength assessed by each user to be higher than a certain predefined value, which offers a minimal nominal throughput. Once the positioning problem is solved, it is then necessary to assign a frequency channel to each mesh router (i.e. access radio interface) in order to communicate with its associated users. In IEEE 802.11-based WLAN, the channel assignment problem consists of assigning radio channels to mesh radio interfaces in such a way that the inter-channel spacing between close mesh routers is maximized. This minimizes  interferences and thus increase the wireless mesh overall network capacity.

However, the problem of backhaul network design can be solved by interconnecting the set of positioned mesh routers among them. The objective here is to select a set of links among all potential links, that allow to connect each mesh router to the gateway. The choice of links to keep has to be done with respect of certain constraints such as the limited number of radio interface, the ripple effect and channel dependency.

The deployment of WMN network is a hard problem and its complexity can not be managed easily even when we tackle with an orderly number of steps. This complexity has lead researchers to propose heuristics in order to deal with the complexity of the  aforementioned multiobjective problems. The optimal deployment of WMN allows to improve the network performance, it is a necessary phase in the design of WMN but not sufficient due to the shared nature of the wireless medium. Thus, the network dimensioning and capacity assignment are other important issues to deal with when designing and deploying wireless mesh networks.

What is a Wireless Mesh Network?

In Carmesh, we are considering urban wireless mesh networks (WMNs) as one option for vehicular connectivity. This kind of network has emerged as a highly flexible, reliable and cost efficient solution for wirelessly covering large areas. It provides low-cost Internet access through multihop communications.

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The Connected Car: A great space for online advertisers

While searching for information on possible services/apps future drivers would really enjoy getting while in their car, I came across this interesting market research report from Arbitron. The findings are based on a broad-based survey with a total of 1,858 peoples interviewed in the US.  The sample is large enough to reveal some general trends, despite the fact that it not clear whether the sample is representative of drivers distribution across US – some findings do suggest that the sample is heavily concentrated in sub-urban areas where driving is King!

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Thoughts on routing aspects with focus on wireless mesh networks

In Carmesh, we are looking at different networking solutions for delivering services to cars, mainly in an urban enviroment. One connectivity solution is wireless mesh networks. One critical aspect of Wireless Mesh Networks (as well as other networks) is routing. That is the focus of this post.

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Enabling VoIP in Wireless Mesh Networks

The digital services that can be provisioned to the car are many and diverse. Let’s imagine a driver (and passengers) of a car connected to the Internet. Every move of the car is fed back to Internet services such as Yelp, Opentable, GMaps, GoCallendar, etc making received services ever more relevant and frictionless. Clearly, the use-case possibilities are endless and the most important are captured in a previous post. In Carmesh, we believe that VoIP services will have a reasonable future in the car. Besides the traditional VoIP chat services (e.g., Skype, Hangout, etc), there are a plethora of services that could be built around tourisms. An example here is a city guided tours service, where a user receives a voice description of landmarks and point of interests depending on its location and driving direction. It is easy to imagine other rich content that can come with the voice such as detailed maps, videos for in-depth coverage of landmarks, reviews, etc.

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Location Based Services: Evolution, Future, and Their Vehicular Destiny

Location based services (LBS) are increasingly an essential part of our digital lives. What started as an add-on to help improve Internet services has today become an intrinsic aspect to the delivery of very many services, especially in the mobile context. For example, mobile apps are increasingly using the users’ location to deliver services such as weather, transportation info, traffic, shopping, and many more.

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