Mobility support is deemed a fundamental service for the next-generation Internet. The current cellular network is the only large-scale infrastructure that successfully provides wide-area, ubiquitous mobility support in reality. With the explosive growth of smartphone devices and the surge of mobile data traffic, cellular networks have been evolving into an increasingly heterogeneous networked system. As a result, managing mobility becomes challenging yet rewarding.
This project seeks to study the configuration issues on mobility management of 2G/3G/4G networks, in order to ensure desirable mobility support. The research focuses on assessing two structural properties: stability and reachability . Stability implies no persistent oscillation loops during constant network conditions, while reachability denotes no access black hole (e.g., certain cells or even a given mobile technology (e.g., 4G) cannot be reached by the device). The success of the project will not only identify and characterize misconfigurations in today's cellular networks, but also protect multi-trillion dollar investment in the fast expanding mobile information infrastructure. The obtained results may influence the design of upcoming 5G wireless networks.
The proposed research has three key areas of technical contributions. First, it takes a novel approach to configuration study. It models and analyzes problematic cases and comes up with a taxonomy of instability and unreachability for the mobility configuration problems, and derives triggering conditions for each problematic instance. The fundamental problem lies in its distributed, yet not well-coordinated configuration decision-making. Second, the project covers activities from theory to practice. Given the misconfiguration instances discovered in theory, it further empirically assesses them in operational mobile networks. It seeks to measure their likelihood in reality and quantify their negative impacts on both the user device and the network infrastructure. The diversified root causes are to be analyzed, spanning policy conflicts within a single parameter, inconsistency between different types of parameters, and uncoordinated decisions between the device and the network. Last, the research proposes new solutions to configuration management in mobile networks. This research simplifies the current approach, while retaining its full configurability for parameters. To this end, two design guidelines of minimal replication of decision rules and no multi-hop mobility decision are explored in order to ensure both stability and reachability of mobility support.
Modeling of Mobility Management
In this work, we focus on two critical properties of the mobility
configuration, which are defined as follows.
Note that the above properties cannot cover all desirable features, but serve as good reference points to
study system-level properties. Moreover, we do not claim that both properties are sufficient to ensure good
design in all cases. Even though both properties are satisfied, the mobility decision can still have issues. For
example, if the 2G's reselection threshold is too rigid, the device may still be trapped in 2G despite good
radio quality from 4G. These are issues incurred by carrier?s preferences or easy-to-fix mistakes.
Our modeling framework covers both mobility schemes for the idle and active states. Given
a user device U, the current serving cell S, and a set of metrics X to be assessed, a mobility decision is
defined as: S x U x X -> T, where T is the target cell. if T = S, it implies that the decision is to
stay at the current cell; otherwise, the device will migrate from S to T.
Our framework further models the following two schemes during idle-state and active-state (RRC connected).
Idle-state Mobility Decision: At the idle state, the device reselects a new serving cell for better network
access later. To this end, the device performs cell (re)selection, a fully standardized decision logic.
The serving cell broadcasts the re-selection parameters to the idle device (listed in Table 1), including the
candidate cells, preference level for each cell, and radio evaluation thresholds for each cell. The device then
selects the target cell among candidates. For each candidate cell, if its priority is higher than the serving
cell, it would be selected if its radio quality is better than the threshold Thresh1. If its priority is lower than
the serving cell, it would be selected if the serving cell?s signal strength is below threshold Thresh3, and
the candidate cell?s radio quality is better than the threshold Thresh2. If its priority is equal to the serving
cell, it would be selected if its signal strength is Hyst offset better than that of the serving cell. If there are
multiple cells satisfying above conditions, the cell with the highest priority would be selected.
Active-state Mobility Decision:
At the active state,
the device actively connects to the serving cell. The
serving cell decides the target cell the device should
move to. Different from the idle-state mobility, there is
no standardized decision logic for the active-state mobility.
The carrier has freedom to customize its decision
logic, metrics to be evaluated, and parameters for
decision-making. However, the 3GPP standards define
several auxiliary configurations to facilitate the active-state
mobility, and the carrier may choose whether/how to use them. Such configurations include: (1) radio
assessment criteria, where the serving cell asks the device to report its perceived radio quality. The criteria
include the candidate cells to be evaluated, the radio thresholds, and the timers for radio evaluation; (2)
traffic evaluation criteria, where the serving cell asks the device to report its traffic load; (3) cell priorities
(e.g., SPID), which are kept internally by the serving cell and help to decide which cell to select; (4) access
control list, which restricts the available target cells.
- Stability: Given any user device U, its serving cell S and metrics X, the converged, target cell T
should remain stable and unchanged. If this property does not hold, persistent loops may occur. The device
would then oscillate between a set of cells, incurring data delay/drops and signaling overhead. We focus on
the persistent loops rather than those transient loops (e.g., the loops caused by radio quality oscillations),
because they have lasting negative impact and can be prevented with proper mobility configuration.
- Reachability: Given a device U, its serving cell S and a target cell T that is available to U at the
given location, there always exists a set of metrics X that (1) given these metrics, the device would be finally
migrated from S to T; (2) these metrics are anticipated by S's mobility decision rules. If this property is
violated, the device may get stuck in S, never reach T, or move to T when S's rules do not intend to.
Instability in Operational Cellular Networks
We identify persistent handoff loops in US carrier networks.
The above figures show a real example observed in our study. This loop occurs between 4G cell (cell 1), 3G Femtocell (cell 2) and 3G Cell (cell 3).
The loop lasts 48 hours and there is no sign to stop. The second plots shows 1-hr log and the 3rd, 4th, 5th plots show the incurred signaling message numbers, the downloading time (of a 5MB file) and webpage loading time (CNN).
The left figure shows the identified loops in two US carriers, spanning 4G, 3G, 3G Femtocells over different bands.
The smallest loop involves 3 cells, while the largest one includes 7 cells.
These happen when they use various RATs (4G, 3G, 2G) or
different frequency bands2. Furthermore, they can be classified
in three categories: 4G-only loop (1), 4G-Femtocell-
3G loops (8 types), 4G-Femtocell-3G-2G loops (8 types),
and 4G-only loop (1 type). Our outdoor tests validates that
all 2G/3G/4G Macrocells have the problematic configurations,
and a potential loop might exist as long as a Femtocell
were deployed at the spots. Based on the loop causes, they can be
further classified in three categories:
C1: uncoordinated handoff goals. In this category, 8 variants
of loops are reported, all happening between 4G Macrocell,
Femtocell and 3G Macrocells. The example in x3 illustrates
the smallest loop here, with c1 = 4G, c2 = Femtocell
and c3 = 3G. These loops are caused by conflicting preference
settings for conflicting goals: the 4G Macrocells intend
to offload user his/her private Femtocells, but 3G Macrocells
prefers to move user to high-speed 4G network.
C2: device-side preference misconfiguration. MMDIAG
further reports 8 variants of loops between 4G Macrocells,
Femtocell, 2G and 3G Macrocells. Compared with previous
category, when leaving the Femtocell, the mobile device
handoffs to 2G first, then handoffs to 3G Macrocells. This
happens when the Femtocell?s signal strength is weak (<-
115dBm) but still higher than 4G?s high-preference handoff
threshold (-116dBm in this scenario)
C3: imprudent 4G infrastructure upgrade. The last variant
is one 4G-only loop. We observe that US-I is upgrading
its 4G infrastructure, and deploying cells under a new frequency
band (c2). Before the upgrade, existing
4G cells (c1 and c3 in Figure 4) assign equal preferences to
each other. US-I intends to migrate users to the new cells,
which offers higher bandwidth. To achieve it, some old cells
(c1) configures new cells with a higher preference. However,
not all cells? preferences are updated timely: preference ties
still happen on some cells (c2).
C4: Uncoordinated load balancing. This is one loop between two 4G cells at one location during active.
Both cells try
to offload the user to each other when both signal strength
are higher than a threshold (here, -106 dBm). However, such
load balancing policies are not coordinated, so the user oscillates
between cells. When both 4G cells have higher -
106dBm Fortunately, this loop is not commonly observed.