SAT SEMINAR SERIES 2013 Glenford Mapp Principal Lecturer, Middlesex University
SAT SEMINAR SERIES2013 Brian Ondiege Ferdinand Katsriku David Silcott Jonathan Loo Haris Pervaiz Qiang Ni
SAT SEMINAR SERIES2013 Motivation for the work Handover Classification Proactive Handover Analysis of Urban/Suburban context Results for Urban/Suburban context Analysis of Motorway context Results for Motorway context Implications for future networking infrastructure (VANETs, etc) Future Plans
SAT SEMINAR SERIES2013 HARDWARE PLATFORM (MOBILE NODE) HARDWARE PLATFORM (BASE STATION) NETWORK ABSTRACTION (MOBILE NODE) NETWORK ABSTRACTION (BASE STATION) VERTICAL HANDOVER POLICY MANAGEMENT END SYSTEM TRANSPORT QOS LAYER APPLICATION ENVIRONMENTS CONFIGURATION LAYER NETWORK MANAGEMENT CORE TRANSPORT NETWORK QOS LAYER SERVICE PLATFORM CORE NETWORK PERIPHERAL NETWORK SAS NTS NAS QBS SECURITY LAYERS
SAT SEMINAR SERIES2013 Can’t explain everything about Y-Comm It’s too big Several institutions work on Y-Comm ◦ Including Middlesex, Cambridge, USP and Lancaster University See Y-Comm Research Webpage: are/ycomm_research.aspx are/ycomm_research.aspx This talk looks at handover issues ◦ In particular we are trying to understand the relationship between handover, the velocity of the mobile node and mobile infrastructure
SAT SEMINAR SERIES2013 Hard vs Soft Handovers ◦ Hard - break before make ◦ Soft – make before break Network vs Client Handovers ◦ Network – network in control (current) ◦ Client – future (Apple’s patent) Upward vs Downward ◦ Upward – smaller to bigger coverage ◦ Downward – bigger to smaller
SAT SEMINAR SERIES2013 HANDOVER IMPERATIVE ALTERNATIVE REACTIVE PROACTIVE KNOWLEDGE-BASED MODEL-BASED NETPREF USERPREF CONTEXT SERVICES UNANTICIPATEDANTICIPATED
SAT SEMINAR SERIES2013 Benefits: ◦ Allows us to minimize disruption due to packet loss or service degradation during handover by signalling to the higher layers that a handover is about to happen ◦ Interested in 2 main parameters Time Before Vertical Handover (TBVH) Network Dwell Time (NDT) – the time a mobile spends in a given network due to mobility
SAT SEMINAR SERIES2013 REQ (Time, TBVH, NDT) A WIRELESS NETWORK TBVH NDT A
SAT SEMINAR SERIES2013 Proactive policies can themselves be divided into 2 types Proactive knowledge-based systems ◦ Knowledge of which local wireless networks are operating at a given location and their strengths at that point ◦ We also need a system to maintain the integrity, accessibility and security of that data
SAT SEMINAR SERIES2013 Knowledge-based approach Gather a database of the field strengths for each network around a city Need to maintain the database and also know how the results might be affected by seasonal effects
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SAT SEMINAR SERIES2013 Uses a simple mathematical model Defines a radius at which handover should occur Finds out how much time I have before I hit that circle (TBVH), given my velocity and direction Used simulation (OPNET) Can be used in the real world as well as in simulation
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SAT SEMINAR SERIES2013 Exit Time (ET) is defined as how much time a mobile node can be in a given network before it must begin handing over to another network ◦ ET is primary dependent on NDT which is in turn dependent on the velocity ◦ T EH – the time taken to handover to the next network
SAT SEMINAR SERIES2013 If ET is less than or equal to zero, then the handover to the first network should not take place as no work will be done because the interface will be forced to immediately begin handing over to the next network This work looks at the effect of this observation on heterogeneous environments ◦ Need to avoid useless handovers
SAT SEMINAR SERIES2013 X NETWORK A NETWORK B
SAT SEMINAR SERIES2013 This was part of David Cottingham’s PhD work. Handover is dependent on 4 delays: ◦ T d is the detection time – time to discover that you are on a new network ◦ T c is the configuration time – time to get and configure your network interface with a new IP address called the Care-of-Address (COA) ◦ T r is called the registration time – time taken to register the new COA with the Home Agent and Corresponding Nodes ◦ T a is called the adaptation time – the time it takes for the higher layers, such as TCP, to make use of the bandwidth of the new network
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SAT SEMINAR SERIES2013 For Reactive Handover we need to add all 4 delays ◦ Because the device is reacting to information from its interfaces, it is not planning ahead For proactive handover, we may avoid the need to add all 4 delays ◦ Because of TBVH, we can signal to the upper layers that handover will occur after a certain time, so they could take evasive action, especially at the transport level
SAT SEMINAR SERIES2013 If we assume the use of low-level triggers and IPv6 auto-configuration techniques ◦ T d and T c are effectively zero So for reactive and proactive handovers we have:
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SAT SEMINAR SERIES2013 NDT in a wireless network is given by the reciprocal of the mobility leave rate. In the literature, the mobility leave rate is given by:
SAT SEMINAR SERIES2013 Assuming circular coverage, we use propagation models to tell us the handover radius for different networks.
SAT SEMINAR SERIES2013 This is highly dependent on the transportation model observed by a population Must be realistic to get good results Two main contexts ◦ Urban/Suburban context ◦ Motorway context
SAT SEMINAR SERIES2013 Urban/Suburban context ◦ Mobile users are everywhere, both pedestrians, people in cars (not the driver, of course!) ◦ Cars observe a maximum velocity or speed limit ◦ Cars and people can mingle; traffic lights, people crossing the road, etc. Motorway context ◦ No pedestrians, mobile users are in cars ◦ Motorways follow well-defined roads We can work out the exact distance between two points on a motorway using GPS ◦ Much higher speed limit compared to the urban/suburban case
SAT SEMINAR SERIES2013 Since pedestrians and cars are mingling and there is a speed limit, V MAX, it is reasonable to set the expected velocity to V MAX /2 ◦ You cannot know every mobile user’s exact NDT so you will have to use a probability distribution So if we plug this into our formula for NDT we get:
SAT SEMINAR SERIES2013 So we found out the expected rate of NDT for different values of V MAX Used an exponential distribution, reasonable in the urban context Decided to use simulation to generate results HANDSIM is a simulation developed by myself and Eser Gemikonakli to study handover The team extended it to look at different velocities and different types of handovers
SAT SEMINAR SERIES2013 So the simulation generated handover requests for different users via a Poisson distribution ◦ At a given maximum velocity, it generated handover requests with a given NDT using the expected value of NDT and the distribution ◦ We then subtracted the handover time for the type of handover being considered from NDT to get the Exit Time. If the Exit Time was less than or equal to zero, that handover request was rejected ◦ We plotted the % rejected handover requests against the maximum velocity
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SAT SEMINAR SERIES2013 WLAN handovers do not do well ◦ Much smaller handover radius ◦ Also the time to handover is fairly long compared to 3G, i.e., 4 seconds for WLANs and 1 second for 3G 3G handovers held their own ◦ Fairly large radius ◦ Handover times are fast for 3G compared to WLAN Proactive handovers did improve the results ◦ Needs further research
SAT SEMINAR SERIES2013 Because mobile users are in cars and we know how to calculate the distance between two points, this means that we can use a different approach We define the Network Dwell Distance (NDD) as the distance travelled along a motorway that is in coverage of a given network NDT = NDD/E(vel)
SAT SEMINAR SERIES2013 There are two instances: ◦ The straight road: in this context we expect that the car will travel at or close to the maximum velocity ◦ The other context is when there is a junction and the car has to slow down to negotiate the junction so the average velocity will fall and so NDT will increase
SAT SEMINAR SERIES2013 F C E H NET B NET A
SAT SEMINAR SERIES2013 F B Z C E G H K Y R2 T w u NET B NET A v
SAT SEMINAR SERIES2013 NET A F C T NET B S E H
SAT SEMINAR SERIES2013 NET A F Z Y C E S T H NET B R BG uv w T D
SAT SEMINAR SERIES2013 At T-junctions, cross-roads or roundabouts we normally stop, so we have a expected velocity of V MAX /2 For other junctions we take the cosine of the angle of the two roads at the junction:
SAT SEMINAR SERIES2013 A B C S T NET A NET B NET C Scenario Three WLANs in a single UMTS cell
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SAT SEMINAR SERIES2013 Straight paths have lower NDD and mobile users travel at close to maximum speed so these sections tend to have lower exit times Junction S had the greater exit time because it had the greater NDD as well as a lower average velocity Junction T did not have as much Exit Time as Junction S because Junction T had a shorter NDD and faster average velocity
SAT SEMINAR SERIES2013 Make the radius of your communication cell larger ◦ WLAN handover radius is too small Intelligent Transport Systems VANET work, Roadside Units (RSU) Handover Radius is 1 Kilometre Modified form of a, higher transmission power Jonathan Loo and others are doing some research on VANETs here at Middlesex So we wanted to see how well this setup would respond to our methods.
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SAT SEMINAR SERIES2013 Towards small cells Allows greater bandwidth But our work shows that there is an issue with small cells and mobility Another way to deal with this is to look at providing joint coverage along a road or highway
SAT SEMINAR SERIES2013 NET A NET B URBAN ROAD P Q
SAT SEMINAR SERIES2013 NET A NET B URBAN ROAD NET C P PQ Q
SAT SEMINAR SERIES2013 Intersect distance for no loss of communication: ◦ PQ >= V MAX * T EH If we want to support a row of intersecting cells along a straight road then: ◦ 2R > 2(V MAX * T EH ) ◦ R > (V MAX * T EH )
SAT SEMINAR SERIES2013 Results for other networks (LTE, etc) ◦ What is the effect of velocity on these networks Handover times and how we could improve them Especially in 4G systems Why is the handover time in WLANs so long! Smaller cell configuration, user mobility and networking infrastructure. ◦ Issues of interference, QoS, etc.
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