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A Smart Decision Model for Vertical Handoff Ling-Jyh Chen * , Tony Sun * , Benny Chen * , Venkatesh Rajendran † , Mario Gerla * * Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA

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A Smart Decision Model for Vertical Handoff

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a smart decision model for vertical handoff

A Smart Decision Model for Vertical Handoff

Ling-Jyh Chen*, Tony Sun*, Benny Chen*,

Venkatesh Rajendran†, Mario Gerla*

* Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA

†Department of Computer Engineering, University of California at Santa Cruz, Santa Cruz, CA 95064, USA

{cclljj, tonysun, cudokido, gerla}@cs.ucla.edu, venkat@soe.ucsc.edu

presentation outline
Presentation Outline
  • Introduction
  • Related Work
  • Smart Decision Model
  • Smart Decision Example
  • Conclusion
problems and solutions
Problems and Solutions
  • Problem
    • Mobile devices with multiple network interfaces today cannot perform handoff among devices without losing existing internet connection—due to change of IP addresses.
  • Solution
    • Universal Seamless Handoff Architecture (USHA) and Handoff Servers (HS).
  • Problem
    • Determining when to handoff to another interface is a complex decision.
  • Solution
    • Smart Decision Model.
definition of handoff
Definition of Handoff
  • Horizontal Handoff
    • Occurs when the user switches between different network access points of the same kind.
    • e.g. Handoff among 802.11 APs.
  • Vertical Handoff
    • Involves two different network interfaces which usually represent different technologies.
    • e.g. Handoff from 802.11 to 1xRTT (CDMA 2000).
seamless handoff
Seamless Handoff
  • Defined as a handoff scheme that maintains the connectivity of all applications on the mobile device when the handoff occurs.
  • Aims to provide continuous end-to-end data service in the face of any link outages or handoff events.
  • Design Goal:
    • low latency
    • Minimal packet loss
related work handoff decision making
Related Work— Handoff Decision-making
  • In “Policy-Enabled Handoffs across Heterogeneous Wireless Networks,” Proc. of ACM WMCSA, 1999, by H.J. Wang, R. H. Katz, and J. Giese:
    • Designed a cost function to decide the best moment and interface for vertical handoff.
    • Cost functions presented in this paper is very preliminary and not able to handle more sophisticated configurations.
    • Logarithmic functions used in the cost function will also have difficulty in representing the cost value while the value of the constraint factor is zero (e.g. the connection is free of charge).
related work handoff decision making10
Related Work— Handoff Decision-making
  • In “CostMetrics For Decision Problem In Wireless Ad Hoc Networking,” IEEE CAS Workshop on Wireless Communications and Networking, 2002, by M. Angermann and J. Kammann:
    • Modeled handoffs with HTTP traffic.
    • May have problems with other types of traffic, such as video and audio streaming, where the bandwidth demand is much higher than HTTP traffic.
testbed universal seamless handoff architecture usha
Testbed: Universal Seamless Handoff Architecture (USHA)

NAT server

All packets are encapsulated and transmitted using UDP

Applications are bound to the tunnel and transparent to the handoff.


smart decision model13
Smart Decision Model
  • With USHA, mobile hosts are able to select any network interface for its connection at any time.
  • However, still need a model that knows which interface to use based on various factors such as
    • Link Capacity (speed)
    • Cost
    • Power Consumption
  • Solution: Smart Decision Model
smart decision model14
HCC—Handoff Control Center

Provides connection between network interfaces and the upper layer applications.

Composed of

DM (Device Monitor)

SM (System Monitor)

SD (Smart Decision)

HE (Handoff Executor)

Smart Decision Model
smart decision model15
DM (Device Monitor)

Monitors and reports the status of each network interface:

Signal strength

Link capacity

Power consumption

SM (System Monitor)

Monitors and reports system information (e.g. current remaining battery)

Smart Decision Model
smart decision model16
SD (Smart Decision)

Integrates user preferences and all other available information provided by DM, SM to achieve a “Smart Decision”

HE (Handoff Executor)

Performs a device handoff if current network interface differs from the one determined by SD.

Smart Decision Model
smart decision process
Smart Decision Process
  • Priority Phase:
    • Add all available interfaces into candidate list.
    • Remove user specified devices from the candidate list.
    • If candidate list is empty, add back removed devices from step 1.
    • Continue with Normal Phase.
  • Normal Phase:
    • Collect information on every wireless interface in the candidate list from the DM component.
    • Collect current system status from SM component.
    • Use the score function to obtain the score of every wireless interface in the candidate list.
    • Handoff all current transmissions to the interface with the highest score if different from current device.
priority normal phases
Priority / Normal Phases
  • Necessary in SD to accommodate user-specific preferences regarding the usage of network interfaces.
    • For instance, a user may decide not to use a device when it causes undesirable interferences to other devices (e.g. 802.11b and 2.4GHz cordless phones).
  • With priority and normal phases in place, the SD module provides flexibility in controlling the desired network interface to the user.
score function
Score Function
  • SD deploys a Score Function to calculate a score for every wireless interface
  • Handoff target device is the network interface with the highest score.
  • Score Function:
    • wj= weight of factor k
    • fj,i = normalized score of interface iof factor j
  • The equation is thus equivalent to:
    • where e = Expense, c = Link Capacity, p = Power Consumption.
score function breakdown
Score Function Breakdown
  • Expense:
  • Link Capacity:
  • Power Consumption:


    • The coefficients α , β , γ are determined by user preference.
    • Inverse functions are used to bound results from 0 to 1.
    • M = Maximum bandwidth requirement demanded by the user.
    • Link capacity is calculated using CapProbe—because advertised link speed is seldom achieved due to link congestion or bad link quality.
smart decision example scenario
Smart Decision Example—Scenario
  • A mobile user currently using 1xRTT on his laptop enters a café.
  • HCC immediately discovers a usable 802.11b access point inside the café and conducts the following comparisons:
    • Expense/Cost:
      • 1xRTT: 1¢/min
      • 802.11b: 10¢/min
    • Link Capacity:
      • 1xRTT: 100 Kbps
      • 802.11b: 5 Mbps
    • Power Consumption (battery time):
      • 1xRTT: 4 hours
      • 802.11b: 2 hours
smart decision example result
Smart Decision Example—Result
  • The mobile user prefers to spend more time in the café and feels that cost and connection speed are equally important to her, thus
    • wp=0.4, we = 0.3, wc = 0.3
  • Coefficient obtained from her preference previously were:
    • αi = xi / 20 , xi :¢/min
    • βi = Min(yi, M)/M , M = 2Mbps
    • γi = 2 / zi , zi : hours
  • Scores calculated using the score function are:
    • S1xRTT = 0.83
    • S802.11b = 0.44.
  • Since S1xRTT > S802.11b , HCC decides to continue using the 1xRTT interface.
  • Smart Decision Model provides a solution for determining the right time to perform handoffs.
  • Our proposed model is able to make smart decisions based on
    • Available network interfaces and properties (e.g. link capacity, power consumption, and link cost).
    • System information (e.g. remaining battery).
    • User preferences.